REFEREED JOURNAL PAPERS (Since 1999)

(Supervised students and postdocs at MSU and TAMUK are underlined)

[445] J. Li, Y. Liu, Z. Zhang, R. Song, Y. Li, and Q. Du, "SWFormer: Stochastic windows convolutional transformer for hybrid modality hyperspectral classification," IEEE Transactions on Image Processing (accepted).

[444] Z. Xiong, W. Li, X. Zhao, B. Zhang, R. Tao, and Q. Du, "PRFNet: A progressive remote sensing image registration and fusion network," IEEE Transactions on Neural Networks and Learning Systems (accepted).

[443] J. Qu, J. Cui, W. Dong, Q. Du, X. Wu, S. Xiao, and Y. Li, "A principle design of registration-fusion consistency: Towards interpretable deep unregistered hyperspectral image fusion," IEEE Transactions on Neural Networks and Learning Systems (accepted).

[442] J. Li, J. Qu, W. Dong, Y. Yang, T. Zhang, Y. Li, and Q. Du, "Cycle-refined multi-decision joint alignment network for unsupervised domain adaptive hyperspectral change detection," IEEE Transactions on Neural Networks and Learning Systems (accepted).

[441] J. Li, S. Du, R. Song, Y. Li, and Q. Du, "Progressive spatial information guided deep aggregation convolutional network for hyperspectral spectral superresolution," IEEE Transactions on Neural Networks and Learning Systems (accepted).

[440] X. Zhang, W. Xie, Y. Li, J. Lei, K. Jiang, L. Fang, and Q. Du, "Block-wise partner learning for model compression," IEEE Transactions on Neural Networks and Learning Systems (accepted).

[439] H. Qin, W. Xie, Y. Li, and Q. Du, "HTD-TS3: Weakly supervised hyperspectral target detection based on transformer via spectral-spatial similarity," IEEE Transactions on Neural Networks and Learning Systems (accepted).

[438] J. Wang, W. Li, Y. Wang, R. Tao, and Q. Du, "Representation-enhanced status replay network for multisource remote sensing image classification," IEEE Transactions on Neural Networks and Learning Systems (accepted).

[437] S. Luo, L. Ma, X. Yang, D. Luo, and Q. Du, "Self-learning based unsupervised domain adaptation for object detection in remote sensing imagery," IEEE Transactions on Geoscience and Remote Sensing (accepted).

[436] H. Su, H. Lu, P. Zheng, H. Zheng, Z. Xue, and Q. Du, "Iterative semi-supervised learning with few-shot samples for coastal wetland land cover classification," IEEE Transactions on Geoscience and Remote Sensing (accepted).

[435] T. Yang, S. Xiao, J. Qu, W. Dong, Q. Du, and Y. Li, "Graph embedding interclass relation-aware adaptive network for cross-scene classification of multisource remote sensing data," IEEE Transactions on Image Processing, vol. 33, 2024.

[434] J. Li. Z. Zhang, R. Song, Y. Li, and Q. Du, "SCFormer: Spectral coordinate transformer for cross-domain few-shot hyperspectral image classification," IEEE Transactions on Image Processing, vol. 33, 2024.

[433] M. Zhang, X. Zhao, W. Li, Y. Zhang, R. Tao, and Q. Du, "Cross-scene joint classification of multisource data with multi-level domain adaption network," IEEE Transactions on Neural Networks and Learning Systems, vol. 35, no. 8, pp. 11514-11526, August 2024.

[432] C. Wu, J. Li, R. Song, Y. Li, and Q. Du, "HPRN: Holistic prior-embedded relation network for spectral super-resolution," IEEE Transactions on Neural Networks and Learning Systems, vol. 35, no. 8, pp. 11409-11423, August 2024.

[431] Z. Fang, W. He, Z. Li, Q. Du, and Q. Chen, "Masked self-distillation domain adaptation for hyperspectral image classification," IEEE Transactions on Geoscience and Remote Sensing, vol. 62, 2024.

[430] J. Li, S. Duan, Y. Leng, R. Song, Y. Li, and Q. Du, "Residual mask in cascaded convolutional transformer for spectral reconstruction," IEEE Transactions on Geoscience and Remote Sensing, vol. 62, 2024.

[429] H. Wang, W. Li, X.-G. Xia, Q. Du, J. Tian, and Q. Shen, "Transformer-based band regrouping with feature refinement for hyperspectral object tracking," IEEE Transactions on Geoscience and Remote Sensing, vol. 62, 2024.

[428] F. Xu, S. Mei, G. Zhang, N. Wang, and Q. Du, "Bridging CNN and Transformer with cross attention fusion network for hyperspectral image classification," IEEE Transactions on Geoscience and Remote Sensing, vol. 62, 2024.

[427] Y.-C. Li, Y.-G. Li, N. Liu, H.-C. Li, and Q. Du, "IDA-SiamNet: Interactive- and dynamic-aware Siamese network for building change detection," IEEE Transactions on Geoscience and Remote Sensing, vol. 62, 2024.

[426] Z. Li, C. Zhang, Y. Wang, W. Li, Q. Du, Z. Fang, and Y. Chen, "Cross-domain few-shot hyperspectral image classification with cross-modal alignment and supervised contrastive learning," IEEE Transactions on Geoscience and Remote Sensing, vol. 62, 2024.

[425] S. Zheng, Z. Wu, Q. Du, Yang Xu, and Z. Wei, "Oriented object detection for remote sensing images via object-wise rotation-invariant semantic representation," IEEE Transactions on Geoscience and Remote Sensing, vol. 62, 2024.

[424] H. Su, D. Shi, Z. Xue, and Q. Du, "Mean-weighted collaborative representation-based spatial-spectral joint classification for hyperspectral images," IEEE Journal of Selected Topics for Applied Earth Observations and Remote Sensing, vol. 17, pp. 10158-10173, 2024.

[423] C. Zhang, H. Su, Z. Wu, Y. Yang, Z. Xue, and Q. Du, "Self-paced probabilistic collaborative representation for anomaly detection of hyperspectral images," IEEE Transactions on Geoscience and Remote Sensing, vol. 62, 2024.

[422] Y. Huang, J. Peng, G. Zhang, W. Sun, N. Chen, and Q. Du, "Adversarial domain adaptation network with calibrated prototype and dynamic instance convolution for hyperspectral image classification," IEEE Transactions on Geoscience and Remote Sensing, vol. 62, 2024.

[421] H. Lu, H. Su, P. Zheng, Y. Gao, H. Zheng, Z. Xue, W. Sun, and Q. Du, "Semi-supervised dynamic ensemble learning method with balancing diversity and consistency for hyperspectral image classification," IEEE Transactions on Geoscience and Remote Sensing, vol. 62, 2024.

[420] H.-C. Li, X.-R. Feng, R.Wang, L. Gao, and Q. Du, "Superpixel-based low-rank tensor factorization for blind nonlinear hyperspectral unmixing," IEEE Sensors Journal, vol. 24, no. 8, April 2024.

[419] Y. Ning, J. Peng, W. Sun, Q. Liu, and Q. Du, "Domain invariant and compact prototype contrast adaptation for hyperspectral image classification," IEEE Transactions on Geoscience and Remote Sensing, vol. 62, 2024.

[418] Y.-J. Deng, M.-L. Yang, H.-C. Li, C.-F. Long, K. Fang, and Q. Du, "Feature dimensionality reduction with L2,p-norm-based robust embedding regression for classification of hyperspectral images," IEEE Transactions on Geoscience and Remote Sensing, vol. 62, 2024.

[417] J. Li, P. Tian, R. Song, H. Xu, Y. Li, and Q. Du, "PCViT: A pyramid convolutional vision transformer detector for object detection in remote sensing imagery," IEEE Transactions on Geoscience and Remote Sensing, vol. 62, 2024.

[416] S. Hu, F. Gao, X. Zhou, J. Dong, and Q. Du, "Hybrid convolutional and attention network for hyperspectral image denoising," IEEE Geoscience and Remote Sensing Letters, vol. 21, 2024.

[415] S. Du, Y. Leng, X. Liang, J. Li, W. Liu, and Q. Du, "Degradation learning unfolding network for hyperspectral image super-resolution," IEEE Geoscience and Remote Sensing Letters, vol. 21, 2024.

[414] J.-Y. Yang, H.-C. Li, J.-H. Yang, L. Pan, Q. Du, and A. Plaza, "Multi-frequency graph convolutional network with cross-modality mutual enhancement for multisource remote sensing data classification," IEEE Transactions on Geoscience and Remote Sensing, vol. 62, 2024.

[413] J. Li, Y. Liu, R. Song, W. Liu, Y. Li, and Q. Du, "HyperMLP: Superpixel prior and feature aggregated perceptron networks for hyperspectral and Lidar hybrid classification," IEEE Transactions on Geoscience and Remote Sensing, vol. 62, 2024.

[412] H. Zhao, S. Liu, X. Tong, Q. Du, L. Bruzzone, K. Du, J. Zhang, X. Lu, "MarsMapNet: A novel superpixel-guided multi-view feature fusion network for efficient Martian landform mapping," IEEE Transactions on Geoscience and Remote Sensing, vol. 62, 2024.

[411] J. Qu, Z. Xu, W. Dong, S. Xiao, Y. Li, and Q. Du, "A spatio-spectral fusion method for hyperspectral images using residual hyper-dense network," IEEE Transactions on Neural Networks and Learning Systems, vol. 35, no. 2, pp. 2235-2249, February 2024.

[410] Y. Zhang, W. Li, M. Zhang, S. Wang, R. Tao, and Q. Du, "Graph information aggregation cross-domain few-shot learning for hyperspectral image classification," IEEE Transactions on Neural Networks and Learning Systems, vol. 35, no. 2, pp. 1912-1925, February 2024.

[409] W. Guo, W. Xie, Y. Li, T. Jiang, and Q. Du, "MMIF: Interpretable hyperspectral and multispectral image fusion via maximum mutual information," IEEE Transactions on Geoscience and Remote Sensing, vol. 62, 2024.

[408] X. He, Y. Chen, L. Huang, D. Hong, and Q. Du, "Foundation model-based multimodal remote sensing data classification," IEEE Transactions on Geoscience and Remote Sensing, vol. 62, 2024.

[407] J. Qu, W. Dong, Y. Li, S. Hou, and Q. Du, "An interpretable unsupervised unrolling network for hyperspectral pansharpening," IEEE Transactions on Cybernetics, vol. 53, no. 12, pp. 7943-7956, December 2023.

[406] J. Wang, W. Li, Y. Gao, M. Zhang, R. Tao, and Q. Du, "Hyperspectral and SAR image classification via multiscale interactive fusion network," IEEE Transactions on Neural Networks and Learning Systems, vol. 34, no. 12, pp. 10823-10837, December 2023.

[405] B. Xi, J. Li, Y. Li, R. Song, Y. Xiao, Q. Du, and J. Chanussot, "Semi-supervised cross-scale graph prototypical network for hyperspectral image classification," IEEE Transactions on Neural Networks and Learning Systems, vol. 34, no. 11, pp. 9337-9351, November 2023.

[404] W. Li, Y. Gao, M. Zhang, R. Tao, and Q. Du, "Asymmetric feature fusion network for hyperspectral and SAR image classification," IEEE Transactions on Neural Networks and Learning Systems, vol. 34, no. 10, pp. 8057-8070, October 2023.

[403] Y. Huang, J. Peng, N. Chen, W. Sun, Q. Du, K. Ren, and K. Huang, "Cross-scene wetland mapping on hyperspectral remote sensing images using adversarial domain adaptation network," ISPRS Journal of Photogrammetry and Remote Sensing, vol. 203, pp. 37-54, September 2023.

[402] H. Zhang, Z. Lin, F. Gao, J. Dong, Q. Du, and H.-C. Li, "Convolution and attention mixed for synthetic aperture radar image change detection," IEEE Geoscience and Remote Sensing Letters, vol. 20, 2023.

[401] L. Ma, S. Li, Z. Zhou, Y. Yao, and Q. Du, "Semantic segmentation network for classification of hyperspectral images with small size samples, " IEEE Geoscience and Remote Sensing Letters, vol. 20, 2023.

[400] J. Lin, F. Gao, X. Shi, J. Dong, and Q. Du, "SS-MAE: Spatial-spectral masked auto-encoder for multi-source image classification," IEEE Transactions on Geoscience and Remote Sensing, vol. 61, 2023.

[399] Y. Li, K. Jiang, W. Xie, J. Lei, X. Zhang, and Q. Du, "A model-driven deep mixture network for robust hyperspectral anomaly detection," IEEE Transactions on Geoscience and Remote Sensing, vol. 61, 2023.

[398] J. Li, Y. Diao, R. Song, B. Xi, Y. Li, and Q. Du, "Class-specific auto-augment architecture based on Schmidt mathematical theory for imbalanced hyperspectral classification," IEEE Transactions on Geoscience and Remote Sensing, vol. 61, 2023.

[397] Q. Liu, J. Peng, N. Chen, W. Sun, Y. Ning, and Q. Du, "Category-specific prototype self-refinement contrastive learning for few-short hyperspectral image classification," IEEE Transactions on Geoscience and Remote Sensing, vol. 61, 2023.

[396] Z. Li, Q. Xu, L. Ma, Z. Fang, Y. Wang, W. He, and Q. Du, "Supervised contrastive learning-based unsupervised domain adaptation for hyperspectral image classification, " IEEE Transactions on Geoscience and Remote Sensing, vol. 61, 2023.

[395] H. Liu, Y. Lu, Z. Wu, Q. Du, J. Chanussot, and Z. Wei, "Spectral variability Bayesian unmixing for hyperspectral sequence in wavelet domain," IEEE Transactions on Geoscience and Remote Sensing, vol. 61, 2023.

[394] H. Lu, H. Su, P. Zheng, Y. Gao, H. Zheng, W. Sun, and Q. Du, "A Probabilistic Sample Boosting Approach with Adaptive Representation Coefficient Consistency for China Coastal Wetland Land Cover Classification Using GF-5 Hyperspectral Imagery," IEEE Transactions on Geoscience and Remote Sensing, vol. 61, 2023.

[393] Z. Li, H. Guo, Y. Chen, C. Liu, Q. Du, Z. Fang, and Y. Wang, "Few-shot hyperspectral image classification with self-supervised learning," IEEE Transactions on Geoscience and Remote Sensing, vol. 61, 2023.

[392] Y. Ning, J. Peng, Q. Liu, Y. Huang, W. Sun, and Q. Du, "Contrastive learning based on category matching for domain adaptation in hyperspectral image classification," IEEE Transactions on Geoscience and Remote Sensing, vol. 61, 2023.

[391] W. Li, Y. Wang, N. Liu, C. Xiao, Z. Sun, and Q. Du, "Integrated spatio-spectral-temporal fusion via anisotropic sparsity constrained low-rank tensor approximation," IEEE Transactions on Geoscience and Remote Sensing, vol. 61, 2023.

[390] Y. Guo, H. Xia, X. Zhao, L. Qiao, Q. Du, and Y. Qin, "Early-season mapping of winter wheat and garlic in Huaihe basin using Sentinel-1/2 and Landsat-7/8 imagery," IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 16, pp. 8809-8817, 2023.

[389] K. Chen, H. Su, G. Yang, and Q. Du, "Unsupervised dimensionality reduction with multi-feature structure joint preserving embedding for hyperspectral imagery," IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing vol. 16, pp. 7585-7599, 2023.

[388] Y. Yang, H. Su, and Q. Du, "Saliency-guided collaborative-competitive representation for hyperspectral anomaly detection," IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 16, pp. 6843-6859, 2023.

[387] Y. Liang, H. Zheng, G. Yang, Q. Du, and H. Su, "Superpixel-based weighted sparse regression and spectral similarity constrained for hyperspectral unmixing," IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing vol. 16, pp. 6825-6842, 2023.

[386] C. O. Ayna, R. Mdrafi, Q. Du, and A. C. Gurbuz, “Learning-based optimization of hyperspectral band selection for classification,” Remote Sensing, vol. 15, 2023

[385] S. Duan, J. Li, R. Song, Y. Li, and Q. Du, "Unmixing-guided convolutional transformer for spectral reconstruction," Remote Sensing, vol. 15, 2023.

[384] H. Su, F. Shao, Y. Gao, H. Zhang, W. Sun, and Q. Du, "Probabilistic collaborative representation based ensemble learning for classification of wetland hyperspectral imagery," IEEE Transactions on Geoscience and Remote Sensing, vol. 61, 2023.

[383] J. Lei, S. Xu, W. Xie, J. Zhang, Y. Li, and Q. Du, "A semantic transferred priori for hyperspectral target detection with spatial-spectral association," IEEE Transactions on Geoscience and Remote Sensing, vol. 61, 2023.

[382] C. Wu, J. Li, R. Song, Y. Li, and Q. Du, "RepCPSI: Coordinate-preserving proximity spectral interaction network with reparameterization for lightweight spectral super-resolution," IEEE Transactions on Geoscience and Remote Sensing, vol. 61, 2023.

[381] J. Li, Y. Leng, R. Song, W. Liu, Y. Li, and Q. Du, "MFormer: Taming masked transformer for unsupervised spectral reconstruction," IEEE Transactions on Geoscience and Remote Sensing, vol. 61, 2023.

[380] M. Ma, S. Mei, F. Li, Y. Ge, and Q. Du, "Spectral correlation based diverse band selection for hyperspectral image classification," IEEE Transactions on Geoscience and Remote Sensing, vol. 61, 2023.

[379] L. Gao, P. Liu, Y. Jiang, W. Xie, J. Lei, Y. Li, and Q. Du, "CBFF-Net: A new framework for efficient and accurate hyperspectral object tracking," IEEE Transactions on Geoscience and Remote Sensing, vol. 61, 2023.

[378] J. Zhang, J. Lei, W. Xie, Z. Fang, Y. Li, and Q. Du, "SuperYOLO: Super resolution assisted object detection in multimodal remote sensing imagery," IEEE Transactions on Geoscience and Remote Sensing, vol. 61, 2023.

[377] L. Gao, X. Sun, X. Sun, L. Zhuang, Q. Du, and B. Zhang, "Hyperspectral anomaly detection based on chessboard topology," IEEE Transactions on Geoscience and Remote Sensing, vol. 61, 2023.

[376] Y. Meng, F. Gao, E. Rigall, R. Dong, J. Dong, and Q. Du, "Physical knowledge enhanced deep neural network for sea surface temperature prediction," IEEE Transactions on Geoscience and Remote Sensing, vol. 61, 2023.

[375] Q. Liu, J. Peng, Y. Ning, N. Chen, W. Sun, Q. Du, and Y. Zhou, "Refined prototypical contrastive learning for few-shot hyperspectral image classification," IEEE Transactions on Geoscience and Remote Sensing, vol. 61, 2023.

[374] J. Peng, L. Yu, N. Chen, W. Sun, and Q. Du, "Two-branch deeper graph convolutional network for hyperspectral image classification," IEEE Transactions on Geoscience and Remote Sensing, vol. 61, 2023.

[373] S. K. Roy, A. Deria, C. Shah, J. M. Haut, Q. Du, and A. Plaza, "Spectral-spatial morphological attention transformer for hyperspectral image classification," IEEE Transactions on Geoscience and Remote Sensing, vol. 61, 2023.

[372] P. Zheng, H. Su, H. Lu, and Q. Du, "Adaptive hypergraph regularized multilayer sparse tensor factorization for hyperspectral unmixing," IEEE Transactions on Geoscience and Remote Sensing, vol. 61, 2023.

[371] M. Wang, F. Gao, J. Dong, H.-C. Li, and Q. Du, "Nearest neighbor-based contrastive learning for hyperspectral and LiDAR data classification,” IEEE Transactions on Geoscience and Remote Sensing, vol. 61, 2023.

[370] L. Qi, Z. Chen, F. Gao, J. Dong, X. Gao, and Q. Du, "Multiview spatial-spectral two-stream network for hyperspectral image unmixing," IEEE Transactions on Geoscience and Remote Sensing, vol. 61, 2023.

[369] M. Zhang, W. Li, X. Zhao, H. Liu, R. Tao, and Q. Du, "Morphological transformation and spatial-logical aggregation for tree species classification using hyperspectral imagery," IEEE Transactions on Geoscience and Remote Sensing, vol. 61, 2023.

[368] Y.-J. Deng, H.-C. Li, S.-Q. Tan, J.-H. Hou, Q. Du, and A. Plaza, "t-Linear tensor subspace learning for robust feature extraction of hyperspectral images," IEEE Transactions on Geoscience and Remote Sensing, vol. 61, 2023.

[367] J. Li, Y. Liu, R. Song, Y. Li, K. Han, and Q. Du, "Sal2RN: A spatial-spectral salient reinforcement network for hyperspectral and LiDAR data fusion classification," IEEE Transactions on Geoscience and Remote Sensing, vol. 61, 2023.

[366] M. Zhang, W. Li, Y. Zhang, R. Tao, and Q. Du, "Hyperspectral and LiDAR data classification based on structural optimization transmission," IEEE Transactions on Cybernetics, vol. 53, no. 5, pp. 3153-3164, May 2023.

[365] X. Zhang, W. Xie, Y. Li, J. Lei, and Q. Du, "Filter pruning via learned representation median in the frequency domain," IEEE Transactions on Cybernetics, vol. 53, no. 5, pp. 3165-3175, May 2023.

[364] H. Qin, W. Xie, Y. Li, K. Jiang, J. Lei, and Q. Du, "Weakly supervised adversarial learning via latent space for hyperspectral target detection," Pattern Recognition, vol. 135, March 2023.

[363] B. K. Ballenger, E. E. Schultz, Q. Du, R. W. Motl, and S. Agiovlasitis, "Calibration of hip-accelerometers for measuring physical activity and sedentary behaviours in adults with Down syndrome," Journal of Intellectual Disability Research, vol. 67, no. 2, pp. 172-181, February 2023.

[362] Y. Zhang, W. Li, R. Tao, W. Sun, and Q. Du, “Single-source domain expansion network for cross-scene hyperspectral image classification,” IEEE Transactions on Image Processing, vol. 32, pp. 1498-1512, 2023.

[361] H. Pan, F. Gao, J. Dong, and Q. Du, “Multi-scale adaptive fusion network for hyperspectral image denoising,” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 16, pp. 3045-3059, 2023.

[360] W. Hou, N. Chen, J. Peng, W. Sun, and Q. Du, "Pyramidal dilation attention convolutional network with active and self-paced learning for hyperspectral image classification," IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 16, pp. 1503-1518, 2023.

[359] T. Zhan, Z. Bi, H. Wu, C. Xu, Q. Du, Y. Xu, and Z. Wu, "A novel cross-scale octave network for hyperspectral and multispectral image fusion," IEEE Transactions on Geoscience and Remote Sensing, vol. 60, December 2022.

[358] T.-Y. Ma, H.-C. Li, R. Wang, Q. Du, X. Jia, and A. Plaza, "Lightweight tensorized neural networks for hyperspectral image classification," IEEE Transactions on Geoscience and Remote Sensing, vol. 60, December 2022.

[357] W. Dong, S. Hou, S. Xiao, J. Qu, Q. Du, and Y. Li, "Generative dual-adversarial network with spectral fidelity and spatial enhancement for hyperspectral pansharpening," IEEE Transactions on Neural Networks and Learning Systems, vol. 33, no. 12, pp. 7303-7317, December 2022.

[356] T. Jiang, W. Xie, Y. Li, J. Lei, and Q. Du, "Weakly supervised discriminative learning with spectral constrained generative adversarial network for hyperspectral anomaly detection," IEEE Transactions on Neural Networks and Learning Systems, vol. 33, no. 11, pp. 6504-6517, November 2022.

[355] K. Jiang, W. Xie, Y. Li, J. Lei, T. Jiang, and Q. Du, "E2E-LIADE: End-to-end local invariant autoencoding density estimation model for anomaly target detection in hyperspectral image," IEEE Transactions on Cybernetics, vol. 52, no. 11, pp. 11385-11396, November 2022.

[354] J. Li, Y. Liu, J. Liu, R. Song, W. Liu, K. Han, and Q. Du, "Feature guide network with context aggregation pyramid for remote sensing image segmentation," IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 15, pp. 9900-9912, 2022.

[353] J. Peng, Y. Huang, W. Sun, N. Chen, and Q. Du, "Domain adaptation in remote sensing image classification: A survey," IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 15, pp. 9842-9859, 2022.

[352] B. Xie, Y. Zhang, S. Mei, G. Zhang, Y. Feng, and Q. Du, "Spectral variation augmented representation for hyperspectral imagery classification with few labeled samples," IEEE Transactions on Geoscience and Remote Sensing, vol. 60, 2022.

[351] H. Zhao, S. Liu, Q. Du, L. Bruzzone, Y. Zheng, K. Du, X. Tong, H. Xie, and X. Ma, "GCFnet: Global collaborative fusion network for multispectral and panchromatic image classification," IEEE Transactions on Geoscience and Remote Sensing, vol. 60, 2022.

[350] Y. Huang, J. Peng, W. Sun, N. Chen, Q. Du, Y. Ning, and H. Su, "Two-branch attention adversarial domain adaptation network for hyperspectral image classification," IEEE Transactions on Geoscience and Remote Sensing, vol. 60, 2022.

[349] J. Li, Y. Ma, R. Song, B. Xi, D. Hong, and Q. Du, "A triplet semi-supervised deep network for fusion classification of hyperspectral and LiDAR Data," IEEE Transactions on Geoscience and Remote Sensing, vol. 60, 2022.

[348] Y. Gao, H. Su, H. Lu, and Q. Du, "Self-balancing dictionary learning for relaxed collaborative representation of hyperspectral image classification," IEEE Transactions on Geoscience and Remote Sensing, vol. 60, 2022.

[347] G. Zhang, S. Mei, B. Xie, Y. Feng, and Q. Du, "Spectral variability augmented two-stream network for hyperspectral sparse unmixing," IEEE Geoscience and Remote Sensing Letters, vol. 19, 2022.

[346] D. Meng, F. Gao, J. Dong, Q. Du, and H.-C. Li, "Synthetic aperture radar image change detection via layer attention-based noise-tolerant network," IEEE Geoscience and Remote Sensing Letters, vol. 19, 2022.

[345] H. Lu, H. Su, P. Zheng, Y. Gao, and Q. Du, "Weighted residual dynamic ensemble learning for hyperspectral image classification," IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 15, pp. 6912-6927, 2022.

[344] H. Su, H. Zhang, Z. Wu, and Q. Du, "Relaxed collaborative representation with low-rank and sparse matrix decomposition for hyperspectral anomaly detection," IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 15, pp. 6826-6842, 2022.

[343] C. Gao, W. Li, R. Tao, and Q. Du, "MS-HLMO: Multi-scale histogram of local main orientation for remote sensing image registration," IEEE Transactions on Geoscience and Remote Sensing, vol. 60, 2022.

[342] W.-S. Hu, H.-C. Li, R. Wang, F. Gao, Q. Du, and A. Plaza, "Pseudo complex-valued deformable ConvLSTM neural network with mutual attention learning for hyperspectral image classification," IEEE Transactions on Geoscience and Remote Sensing, vol. 60, 2022.

[341] J. Lei, P. Liu, W. Xie, L. Gao, Y. Li, and Q. Du, "Spatial-spectral cross-correlation embedded dual-transfer network for object tracking using hyperspectral videos," Remote Sensing, vol. 14, no. 15, July 2022.

[340] N. Wang, W. Li, R. Tao, and Q. Du, "Graph-based block-level urban change detection using Sentinel-2 time series," Remote Sensing of Environment, vol. 274, June 2022.

[339] W. Dong, J. Qu, T. Zhang, Y. Li, and Q. Du, "Context-aware guided attention based cross-feedback dense network for hyperspectral image super-resolution," IEEE Transactions on Geoscience and Remote Sensing, vol. 60, 2022.

[338] S. Liu, Y. Zheng, Q. Du, L. Bruzzone, A. Samat, X. Tong, Y. Jin, and C. Wang, "A shallow-to-deep feature fusion network for VHR remote sensing image classification," IEEE Transactions on Geoscience and Remote Sensing, vol. 60, 2022.

[337] N. Liu, W. Li, R. Tao, Q. Du, and J. Chanussot, "Multi-graph-based low-rank tensor approximation for hyperspectral image restoration," IEEE Transactions on Geoscience and Remote Sensing, vol. 60, 2022.

[336] K. He, W. Sun, G. Yang, X. Meng, K. Ren, J. Peng, and Q. Du, "A dual global-local attention network for hyperspectral band selection," IEEE Transactions on Geoscience and Remote Sensing, vol. 60, 2022.

[335] Z. Fang, Y. Yang, Z. Li, W. Li, Y. Chen, L. Ma, and Q. Du, "Confident learning-based domain adaptation for hyperspectral image classification," IEEE Transactions on Geoscience and Remote Sensing, vol. 60, 2022.

[334] G. Zhang, S. Mei, B. Xie, M. Ma, Y. Zhang, Y. Feng, and Q. Du, "Spectral variability augmented sparse unmixing of hyperspectral images," IEEE Transactions on Geoscience and Remote Sensing, vol. 60, 2022.

[333] J. Lei, Y. Gu, W. Xie, Y. Li, and Q. Du, "Boundary extraction constrained siamese network for remote sensing image change detection," IEEE Transactions on Geoscience and Remote Sensing, vol. 60, 2022.

[332] Y. Yang, J. Qu, S. Xiao, W. Dong, and Q. Du, "A deep multiscale pyramid network enhanced with spatial-spectral residual attention for hyperspectral image change detection," IEEE Transactions on Geoscience and Remote Sensing, vol. 60, 2022.

[331] H. Su, Y. Gao, and Q. Du, "Superpixel-based relaxed collaborative representation with band-weighting for hyperspectral image classification," IEEE Transactions on Geoscience and Remote Sensing, vol. 60, 2022.

[330] Y. Ning, J. Peng, L. Sun, Y. Huang, W. Sun, and Q. Du, "Adaptive local discriminant analysis and distribution matching for domain adaptation in hyperspectral image classification," IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing vol. 15, pp. 4797-4808, 2022.

[329] X.-R. Feng, H.-C. Li, R. Wang, Q. Du, X. Jia, and A. Plaza, "Hyperspectral unmixing based on nonnegative matrix factorization: A comprehensive review," IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 15, pp. 4414-4436, 2022.

[328] H. Su, Y. Hu, H. Lu, W. Sun, and Q. Du, "Diversity-driven multi-kernel collaborative representation ensemble for hyperspectral image classification," IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 15, pp. 2861-2876, 2022.

[327] H. Lu, H. Su, J. Hu, and Q. Du, "Dynamic ensemble learning multi-view kernel collaborative subspace clustering for hyperspectral image classification," IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 15, pp. 2681-2695, 2022.

[326] J. Wang, F. Gao, J. Dong, Q. Du, and H.-C. Li, "Change detection from synthetic aperture radar images via dual path denoising network," IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 15, pp. 2667-2680, 2022.

[325] J. Li, S. Zi, R. Song, Y. Li, Y. Hu, and Q. Du, "A stepwise domain adaptive segmentation network with covariate shift alleviation for remote sensing imagery," IEEE Transactions on Geoscience and Remote Sensing, vol. 60, 2022.

[324] Y. Liu, W. Xie, Y. Li, Z. Li, and Q. Du, "Dual-frequency autoencoder for anomaly detection in transformed hyperspectral imagery," IEEE Transactions on Geoscience and Remote Sensing, vol. 60, 2022.

[323] L. Qi, F. Gao, J. Dong, X. Gao, and Q. Du, "SSCU-Net: Spatial-spectral collaborative unmixing network for hyperspectral images," IEEE Transactions on Geoscience and Remote Sensing, vol. 60, 2022.

[322] J. Li, S. Du, R. Song, C. Wu, Y. Li, and Q. Du, "HASIC-net: Hybrid attentional convolutional network with structure information consistency for spectral super-resolution of RGB images," IEEE Transactions on Geoscience and Remote Sensing, vol. 60, 2022.

[321] X. Zhang, W. Xie, Y. Li, J. Lei, and Q. Du, "Rank-aware generative adversarial network for hyperspectral band selection," IEEE Transactions on Geoscience and Remote Sensing, vol. 60, 2022.

[320] J. Qu, Y. Xu, W. Dong, Y. Li, and Q. Du, "Dual-branch difference amplification graph convolutional network for hyperspectral image change detection," IEEE Transactions on Geoscience and Remote Sensing, vol. 60, 2022.

[319] S. Liu, H. Zhao, Q. Du, L. Bruzzone, A. Samat, and X. Tong, "Novel cross-resolution feature-level fusion for joint classification of multispectral and panchromatic remote sensing images," IEEE Transactions on Geoscience and Remote Sensing, vol. 60, 2022.

[318] B. K. Ballenger, E. E. Schultz, M. Driskill, S. Richardson, Q. Du, R. W. Motl, and S. Agiovlasitis, “Accelerometer-based estimation of oxygen uptake in adults with Down syndrome: vector magnitude vs. vertical axis,” Journal of Intellectual Disability Research, vol. 66, no. 4, pp. 368-375, April 2022.

[317] B. Xie, S. Mei, G. Zhang, Y. Zhang, Y. Feng, and Q. Du, "Extended collaborative representation-based hyperspectral imagery classification," IEEE Geoscience and Remote Sensing Letters, vol. 19, March 2022.

[316] X. Wu, W. Li, D. Hong, R. Tao, and Q. Du, "Deep learning for UAV-based object detection and tracking: A survey," IEEE Geoscience and Remote Sensing Magazine, vol. 10, no. 1, pp. 91-124, March 2022.

[315] H. Su, Z. Wu, H. Zhang, and Q. Du, "Hyperspectral anomaly detection: A survey," IEEE Geoscience and Remote Sensing Magazine, vol. 10, no. 1, pp. 64-90, March 2022.

[314] J. Peng, W. Sun, H.-C. Li, W. Li, X. Meng, C. Ge, and Q. Du, "Low-rank and sparse representation for hyperspectral image processing: A review," IEEE Geoscience and Remote Sensing Magazine, vol. 10, no. 1, pp. 10-43, March 2022.

[313] L. Li, W. Li, C. Zhao, Y. Qu, R. Tao, and Q. Du, "Prior-based tensor representation for anomaly detection in hyperspectral imagery," IEEE Transactions on Neural Networks and Learning Systems, vol. 33, no. 3, pp. 1037-1050, March 2022.

[312] Y. Liu, Q. Li, Q. Du, and Q. Wang, "ABNet: Adaptive balanced network for multi-scale object detection in remote sensing imagery," IEEE Transactions on Geoscience and Remote Sensing, vol. 60, 2022.

[311] J. Wang, F. Gao, J. Dong, S. Zhang, and Q. Du, "Change detection from synthetic aperture radar images via graph-based knowledge supplement network," IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 15, pp. 1823-1836, 2022.

[310] J. Qu, S. Hou, W. Dong, S. Xiao, Q. Du, and Y. Li, "A dual-branch detail extraction network for hyperspectral pansharpening," IEEE Transactions on Geoscience and Remote Sensing, vol. 60, 2022.

[309] H.-C. Li, W.-S. Hu, W. Li, J. Li, Q. Du, and A. Plaza, "A³CLNN: Spatial attention, spectral attention, and multi-scale attention ConvLSTM neural network for multisource remote sensing data classification," IEEE Transactions on Neural Networks and Learning Systems, vol. 33, no. 2, pp. 747-761, February 2022.

[308] C. Shah, Q. Du, and Y. Xu, "Enhanced TabNet: Attentive interpretable tabular learning for hyperspectral image classification," Remote Sensing, vol.14, 2022.

[307] H.-C. Li, X.-R. Feng, D. Zhai, Q. Du, and A. Plaza, "Self-supervised robust deep matrix factorization for hyperspectral unmixing," IEEE Transactions on Geoscience and Remote Sensing, vol 60, 2022.

[306] W. Sun, J. Peng, W. Li, H.-C. Li, G. Yang, X. Meng, and Q. Du, "A multiscale spectral features graph fusion method for hyperspectral band selection," IEEE Transactions on Geoscience and Remote Sensing, vol. 60, 2022.

[305] J. Li, H. Zhang, R. Song, W. Xie, Y. Li, and Q. Du, "Structure-guided feature transform hybrid residual network for remote sensing object detection," IEEE Transactions on Geoscience and Remote Sensing, vol. 60, 2022.

[304] Y. Li, T. Jiang, W. Xie, J. Lei, and Q. Du, "Sparse coding-inspired GAN for hyperspectral anomaly detection in weakly supervised learning," IEEE Transactions on Geoscience and Remote Sensing, vol. 60, 2022.

[303] S. Mei, X. Li, X. Lin, H. Cai, and Q. Du, "Hyperspectral image classification using attention-based bidirectional long short-term memory network," IEEE Transactions on Geoscience and Remote Sensing, vol 60, 2022.

[302] Y. Gao, W. Li, M. Zhang, J. Wang, W. Sun, R. Tao, and Q. Du, "Hyperspectral and multispectral classification for coastal wetland based on deepwise feature interaction network," IEEE Transactions on Geoscience and Remote Sensing, vol. 60, 2022.

[301] M. Zhang, W. Li, R. Tao, H.-C. Li, and Q. Du, "Information fusion for classification of hyperspectral and LiDAR data using IP-CNN," IEEE Transactions on Geoscience and Remote Sensing, vol. 60, 2022.

[300] Z. Hou, W. Li, L. Li, R. Tao, and Q. Du, "Hyperspectral change detection based on multiple morphological filters," IEEE Transactions on Geoscience and Remote Sensing, vol. 60, 2022.

[299] Q. Liu, Z. Wu, Q. Du, Y. Xu, and Z. Wei, "Multi-scale alternately updated clique network for hyperspectral image classification," IEEE Transactions on Geoscience and Remote Sensing, vol. 60, 2022.

[298] W. Xie, S. Fan, J. Qu, Y. Lu, and Q. Du, "Spectral distribution-aware estimation network for hyperspectral anomaly detection," IEEE Transactions on Geoscience and Remote Sensing, vol. 60, 2022.

[297] Y. Wang, M. Liu, Z. Li, Q. Du, Y. Chen, F. Li, and H. Yang, "Heterogeneous few-shot learning for hyperspectral image classification," IEEE Geoscience and Remote Sensing Letters, vol. 19, 2022.

[296] J.-Y Yang, H.-C. Li, W.-S. Hu, L. Pan, and Q. Du, "Adaptive cross-attention-driven spatial-spectral graph convolutional network for hyperspectral image classification," IEEE Geoscience and Remote Sensing Letters, vol. 19, 2022.

[295] Y. Shen, C. Chen, L. Xiao, and Q. Du, "BDANet: Multiscale convolutional neural network with cross-directional attention for building damage assessment from satellite images," IEEE Transactions on Geoscience and Remote Sensing, vol. 60, 2022.

[294] H. Su, C. Jia, P. Zheng, and Q. Du, "Superpixel-based weighted collaborative sparse regression and reweighted low-rank representation for hyperspectral image unmixing," IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 15, pp. 393-408, 2022.

[293] W. Dong, Y. Yang, J. Qu, and Q. Du, "Hyperspectral pansharpening algorithm via local intensity component estimation," IEEE Geoscience and Remote Sensing Letters, vol. 19, 2022.

[292] X. Chen, L. Ma, and Q. Du, "Oriented object detection by searching corner points in remote sensing imagery," IEEE Geoscience and Remote Sensing Letters, vol. 19, 2022.

[291] C. Shah and Q. Du, "Spatial-aware collaboration-competition preserving graph embedding for hyperspectral image classification," IEEE Geoscience and Remote Sensing Letters, vol. 19, 2022.

[290] X. Qu, F. Gao, J. Dong, Q. Du, and H.-C. Li, "Change detection in synthetic aperture radar images using a dual-domain network," IEEE Geoscience and Remote Sensing Letters, vol. 19, 2022.

[289] T. Zhang, F. Gao, J. Dong, and Q. Du, "Remote sensing image translation via style-based recalibration module and improved style discriminator," IEEE Geoscience and Remote Sensing Letters, vol. 19, 2022.

[288] J. Qu, Y. Shi, W. Xie, Y. Li, X. Wu, and Q. Du, "MSSL: Hyperspectral and panchromatic image fusion via multiresolution spatial-spectral feature learning networks," IEEE Transactions on Geoscience and Remote Sensing, vol. 60, 2022.

[287] X. Song, H.-C. Li, L. Pan, Y.-J. Deng, L. You, P. Zhang, and Q. Du, "Unsupervised robust projection learning by low-rank and sparse decomposition for hyperspectral feature extraction," IEEE Geoscience and Remote Sensing Letters, vol. 19, 2022.

[286] H. Liu, Y. Lu. Z. Wu, Q. Du, J. Chanussot, and Z. Wei, "Bayesian unmixing of hyperspectral image sequence with composite priors for abundance and endmember variability," IEEE Transactions on Geoscience and Remote Sensing, vol. 19, 2022.

[285] H.-C. Li, S. Li, W. Hu, J. Feng, W. Sun, and Q. Du, "Recurrent feedback convolutional neural network for hyperspectral image classification," IEEE Geoscience and Remote Sensing Letters, vol. 19, 2022.

[284] Y. Xu, Z. Li, W. Li, Q. Du, C. Liu, Z. Fang, and L. Zhai, "Dual channel residual network for hyperspectral image classification with noisy labels," IEEE Transactions on Geoscience and Remote Sensing, vol. 60, 2022.

[283] Z. Li, M. Liu, Y. Chen, Y. Xu, W. Li, and Q. Du, "Deep cross-domain few-shot learning for hyperspectral image classification," IEEE Transactions on Geoscience and Remote Sensing, vol. 60, 2022.

[282] B. Xi, J. Li, Y. Li, R. Song, Y. Xiao, Y. Shi, and Q. Du, "Multi-direction networks with attentional spectral prior for hyperspectral image classification," IEEE Transactions on Geoscience and Remote Sensing, vol. 60, 2022.

[281] W. Sun, J. Peng, G. Yang, X. Meng, and Q. Du, "Multiscale low-rank spatial features for hyperspectral image classification," IEEE Geoscience and Remote Sensing Letters, vol. 19, 2022.

[280] J. Peng, W. Sun, F. Jiang, H. Chen, Y. Zhou, and Q. Du, "A general loss-based nonnegative matrix factorization for hyperspectral unmixing," IEEE Geoscience and Remote Sensing Letters, vol. 19, 2022.

[279] Y. Gao, F. Gao, J, Dong, Q. Du, and H.-C. Li, "Synthetic aperture radar image change detection via Siamese adaptive fusion network," IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 14, pp. 10748-10760, 2021.

[278] Y. Zheng, S. Liu, Q. Du, H. Zhao, X. Tong, and M. Dalponte, "A novel multitemporal deep fusion network (MDFN) for short-term multitemporal HR images classification," IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 14, pp. 10691-10703, 2021.

[277] Y. Zhang, W. Li, R. Tao, J. Peng, and Q. Du, "Cross-scene hyperspectral classification with discriminative cooperative alignment," IEEE Transactions on Geoscience and Remote Sensing, vol. 59, no. 11, pp. 9646-9660, November 2021.

[276] J. Qu, Q. Du, Y. Li, L. Tian, and H. Xia, "Anomaly detection in hyperspectral imagery using Gaussian mixture model," IEEE Transactions on Geoscience and Remote Sensing, vol. 59, no. 11, pp. 9504-9516, November 2021.

[275] S. Yang, J. Hou, Y. Jia, S. Mei, and Q. Du, "Subpixel-guided discriminative low-rank representation of hyperspectral images for classification," IEEE Transactions on Image Processing, vol. 30, pp. 8823-8835, 2021.

[274] B. Wang, S. Zhang, Y. Feng, S. Mei, S. Jia, and Q. Du, “Hyperspectral imagery spatial super-resolution using generative adversarial network,” IEEE Transactions on Computational Imaging, vol. 7, pp. 948-960, 2021.

[273] L. Li, W. Li, Q. Du, and R. Tao, "Low-rank and sparse decomposition with Mixture-of-Gaussian for anomaly detection in hyperspectral imagery," IEEE Transactions on Cybernetics, vol. 51, no. 9, pp. 4363-4372, September 2021.

[272] Y. Huang, J. Peng, Y. Ning, W. Sun, and Q. Du, "Graph embedding and distribution alignment for domain adaptation in hyperspectral image classification," IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 14, pp. 7654-7666, 2021.

[271] Y. Zhu, W. Li, M. Zhang, Y. Pang, R. Tao, and Q. Du, "Joint feature extraction for multi-source data using similar double-concentrated network," Neurocomputing, vol. 450, pp. 70-79, August 2021.

[270] W. Xie, X. Zhang, Y. Li, J. Lei, J. Li, and Q. Du, "Weakly supervised low-rank representation for hyperspectral anomaly detection," IEEE Transactions on Cybernetics, vol. 51, no. 8, pp. 3889-3900, August 2021.

[269] G. Li, Y. Xiong, Q. Du, Z. Shi, and R. S. Gates, "Classifying ingestive behavior of dairy cows via automatic sound recognition," Sensors, vol. 21, 2021.

[268] Q. Du, B. Tang, W. Xie, and W. Li, "Parallel and distributed computing for anomaly detection from hyperspectral remote sensing imagery," Proceedings of the IEEE, vol. 109, no. 8, pp. 1306-1319, August 2021.

[267] Y. Shi, J. Li, Y. Li, and Q. Du, "Sensor-independent hyperspectral target detection with semi-supervised domain adaptive few-shot learning," IEEE Transactions on Geoscience and Remote Sensing, vol. 59, no. 8, pp. 6894-6906, August 2021.

[266] H. Su, Y. Yu, Z. Wu, Q. Du, and P. Du, "Random subspace-based K-nearest class collaborative representation for hyperspectral image classification," IEEE Transactions on Geoscience and Remote Sensing, vol. 59, no. 8, pp. 6840-6853, August 2021.

[265] W. Sun, G. Yang, K. Ren, J. Peng, C. Ge, X. Meng, and Q. Du, "A label similarity probability filter for hyperspectral image post-classification," IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 14, pp. 6897-6905, 2021.

[264] G. Zhang, S. Mei, Y. Feng, and Q. Du, "Spectral-spatial constrained nonnegative matrix factorization for spectral mixture analysis of hyperspectral images," IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 14, pp. 6766-6776, 2021.

[263] Z. Hou, W. Li, R. Tao, and Q. Du, "Three-order Tucker decomposition and reconstruction detector for unsupervised hyperspectral change detection," IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 14, pp. 6194-6205, 2021.

[262] Y. Shen, S. Zhu, C. Chen, Q. Du, L. Xiao, J. Chen, and D. Pan, "Efficient deep learning of non-local features for hyperspectral image classification," IEEE Transactions on Geoscience and Remote Sensing, vol. 59, no. 7, pp. 6029-6043, July 2021.

[261] J. Zhong, W. Xie, Y. Li, J. Lei, and Q. Du, "Characterization of background-anomaly separability with generative adversarial network for hyperspectral anomaly detection," IEEE Transactions on Geoscience and Remote Sensing, vol. 59, no. 7, pp. 6017-6028, July 2021.

[260] S. Mei, K. Yan, M. Ma, X. Chen, S. Zhang, and Q. Du, "Remote sensing scene classification using sparse representation-based framework with deep feature fusion," IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 14, pp. 5867-5878, 2021.

[259] C. Shah and Q. Du, "Collaborative and low-rank graph for discriminant analysis of hyperspectral imagery," IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 14, pp. 5248-5259, 2021.

[258] B. Xi, J. Li, Y. Li, R. Song, W. Sun, and Q. Du, "Multiscale context-aware ensemble deep KELM for efficient hyperspectral image classification," IEEE Transactions on Geoscience and Remote Sensing vol. 59, no. 6, pp. 5114-5130, June 2021.

[257] J. Wang, F. Gao, J. Dong, and Q. Du, "Adaptive dropblock enhanced generative adversarial networks for hyperspectral image classification," IEEE Transactions on Geoscience and Remote Sensing, vol. 59, no. 6, pp. 5040-5053, June 2021.

[256] D. Hong, L. Gao, N. Yokoya, J. Yao, J. Chanussot, Q. Du, and B. Zhang, "More diverse means better: Multimodal deep learning meets remote sensing imagery classification," IEEE Transactions on Geoscience and Remote Sensing, vol. 59, no. 5, pp. 4340-4354, May 2021.

[255] W.-S. Hu, H.-C. Li, Y.-J. Deng, Q. Du, and A. Plaza, "Lightweight tensor attention-driven ConvLSTM neural network for hyperspectral image classification," IEEE Journal of Selected Topics in Signal Processing, vol. 15, no. 3, pp. 734-745, April 2021.

[254] W. Wang, L. Ma, M. Chen, and Q. Du, "Joint correlation alignment based graph neural network for domain adaptation of multitemporal hyperspectral remote sensing images," IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 14, pp. 3170-3184, 2021.

[253] W.-Y. Wang, H.-C. Li, Y.-J. Deng, X. Lu, and Q. Du, "Generative adversarial capsule network with convLSTM for hyperspectral image classification," IEEE Geoscience and Remote Sensing Letters, vol. 18, no. 3, pp. 523-527, March 2021.

[252] C. Ge, Q. Du, W. Sun, K. Wang, J. Li, and Y. Li, "Deep residual network-based fusion framework for hyperspectral and LiDAR data," IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 14, pp. 2458-2472, 2021.

[251] J. Peng, Y. Zhou, W. Sun, Q. Du, and L. Xia, "Self-paced nonnegative matrix factorization for hyperspectral unmixing," IEEE Transactions on Geoscience and Remote Sensing, vol. 59, no. 2, pp. 1501-1515, February 2021.

[250] H. Wei, L. Ma, Y. Liu, and Q. Du, "Combining multiple classifiers for domain adaptation of remote sensing image classification," IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 14, pp. 1832-1847, 2021.

[249] P. Zhang, H. Su, and Q. Du, "Sparse and low-rank constrained tensor factorization for hyperspectral image unmixing," IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 14, pp. 1754-1767, 2021.

[248] L. Li, H. Su, P. Zheng, Q. Du, and T. Wu, "A novel surface water index using local background information for long term and large-scale Landsat images," ISPRS Journal of Photogrammetry and Remote Sensing, vol. 172, pp. 59-78, February 2021.

[247] C. Liu, R. Tao, W. Li, M. Zhang, W. Sun, and Q. Du, "Joint classification of hyperspectral and multispectral images for mapping coastal wetlands," IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 14, pp. 982-996, 2021.

[246] S. Liu, Q. Du, A. Samat, X. Tong, and M. Dalponte, "A novel feature fusion approach for VHR remote sensing image classification," IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 14, pp. 464-473, 2021.

[245] Z. Liu, L. Ma, and Q. Du, "Class-wise distribution adaptation for unsupervised classification of hyperspectral remote sensing images," IEEE Transactions on Geoscience and Remote Sensing, vol. 59, no. 1, pp. 463-477, January 2021.

[244] W. Xie, Y. Cui, Y. Li, J. Lei, Q. Du, and J. Li, "HPGAN: Hyperspectral pansharpening using 3D generative adversarial networks," IEEE Transactions on Geoscience and Remote Sensing, vol. 59, no. 1, pp. 463-477, January 2021.

[243] H. Su, W. Yao, Z. Wu, P. Zheng, and Q. Du, "Kernel low-rank representation with elastic net for China coastal wetland land cover classification using GF-5 hyperspectral imagery," ISPRS Journal of Photogrammetry and Remote Sensing, vol. 171, pp. 238-252, January 2021.

[242] K. Tan, W. Ma, L. Chen, H. Wang, Q. Du, P. Du, B. Yan, R. Liu, and H. Li, "Estimating the distribution trend of soil heavy metals in mining area from HyMap airborne hyperspectral imagery based on ensemble learning," Journal of Hazardous Materials, vol. 401, January 2021.

[241] R. H. MD Rafi, Q. Du, A. Gurbuz, B. Tang, L. Ma, and N. H. Younan, "Attention-based domain adaptation using residual network for hyperspectral image classification," IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 13, pp. 6424-6433, 2020.

[240] M. Chen, L. Ma, W. Wang, and Q. Du, "Augmented associate learning based domain adaptation for classification of hyperspectral remote sensing images," IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 13, pp. 6236-6248, 2020.

[239] W. Xie, X. Zhang, Y. Li, K. Wang, and Q. Du, "Background learning based on target suppression constraint for hyperspectral target detection," IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 13, pp. 5872-5882, 2020.

[238] H.-C. Li, W. Wang, S. Ye, Y. Deng, F. Zhang, and Q. Du, "A mixture generative adversarial network with category multi-classifier for hyperspectral image classification," Remote Sensing Letters, vol. 11, no. 11, pp. 983-992, November 2020.

[237] H. Su, Z. Wu, A.-X. Zhu, and Q. Du, "Low-rank and collaborative representation for hyperspectral anomaly detection via robust dictionary construction," ISPRS Journal of Photogrammetry and Remote Sensing, vol. 169, pp. 195-211, November 2020.

[236] T. Li, Q. Meng, and Q. Du, "Application of random effects to explore the Gulf of Mexico coastal forest dynamics in relation to meteorological factors," IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 13, pp. 5526-5535, 2020.

[235] X. Zhao, R. Tao, W. Li, H.-C. Li, Q. Du, W. Liao, and W. Philips, "Joint classification of hyperspectral and LiDAR data using hierarchical random walk and deep CNN architecture," IEEE Transactions on Geoscience and Remote Sensing, vol. 58, no. 10, pp. 7355-7370, October 2020.

[234] X. Wu, W. Li, D. Hong, J. Tian, R. Tao, and Q. Du, "Vehicle detection of multi-source remote sensing data using active fine-tuning network," ISPRS Journal of Photogrammetry and Remote Sensing, vol. 167, no. 39-53, September 2020.

[233] Y. Zhang, T. Wang, S. Mei, and Q. Du, "Subpixel mapping of hyperspectral images using a labeled-unlabeled hybrid endmember library and abundance optimization," IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 13, pp. 5036-5047, September 2020.

[232] S. Yang, J. Hou, Y. Jia, S. Mei, and Q. Du, "Hyperspectral image classification with incremental sparse representation," IEEE Geoscience and Remote Sensing Letters, vol. 17, no. 9, pp. 1598-1602, September 2020.

[231] Y. Zhao, G. Li, J. Purswell, D. Chesser, W. Lowe, and Q. Du, "Analysis of feeding and drinking behaviors of group-reared broilers via image processing," Computers and Electronics in Agriculture, vol. 175, 2020.

[230] X. Wang, K. Tan, Q. Du, Y. Chen, and P. Du, "CVA²E: A conditional variational autoencoder with an adversarial training process for hyperspectral image classification," IEEE Transactions on Geoscience and Remote Sensing, vol. 58, no. 8, pp. 5676-5692, August 2020.

[229] W. Xie, B. Liu, Y. Li, J. Lei, and Q. Du, "Autoencoder and adversarial-learning based semi-supervised background estimation for hyperspectral anomaly detection," IEEE Transactions on Geoscience and Remote Sensing, vol. 58, no. 8, pp. 5416-5427, August 2020.

[228] B. Xi, J. Li, Y. Li, Y. Shi, R. Song, and Q. Du, "Deep prototypical networks with hybrid residual attention for hyperspectral image classification," IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 13, pp. 3683-3700, 2020.

[227] S. Mei, G. Zhang, J. Li, Y. Zhang, and Q. Du, "Improving spectral-based endmember finding by exploring spatial context for hyperspectral unmixing," IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 13, pp. 3336-3349, 2020.

[226] K. Jiang, W. Xie, Y. Li, J. Lei, G. He, and Q. Du, "Semi-supervised spectral learning with generative adversarial network for hyperspectral anomaly detection," IEEE Transactions on Geoscience and Remote Sensing, vol. 58, no. 7, pp. 5224-5236, July 2020.

[225] T. Jiang, Y. Li, W. Xie, and Q. Du, "Discriminative reconstruction constrained generative adversarial network for hyperspectral anomaly detection," IEEE Transactions on Geoscience and Remote Sensing, vol. 58, no. 7, pp. 4666-4679, July 2020.

[224] S. Mei, R. Jiang, X. Li, and Q. Du, "Spatial and spectral joint super-resolution using convolutional neural network," IEEE Transactions on Geoscience and Remote Sensing, vol. 58, no. 7, pp. 4590-4603, July 2020.

[223] J. Li, B. Li, R. Song, Y. Li, Y. Dai, and Q. Du, "Hyperspectral image super-resolution by band attention through adversarial learning," IEEE Transactions on Geoscience and Remote Sensing, vol. 58, no. 6, pp. 4304-4318, June 2020.

[222] W.-S. Hu, H.-C. Li, L. Pan, W. Li, R. Tao, and Q. Du, "Spatial-spectral feature extraction via deep ConvLSTM neural networks for hyperspectral image classification," IEEE Transactions on Geoscience and Remote Sensing, vol. 58, no. 6, pp. 4237-4250, June 2020.

[221] W. Sun, J. Peng, G. Yang, and Q. Du, "Fast and latent low-rank subspace clustering for hyperspectral band selection," IEEE Transactions on Geoscience and Remote Sensing, vol. 58, no. 6, pp. 3906-3915, June 2020.

[220] H. Su, Y. Yu, Q. Du, and P. Du, "Ensemble learning for hyperspectral image classification using tangent collaborative representation," IEEE Transactions on Geoscience and Remote Sensing, vol. 58, no. 6, pp. 3778-3790, June 2020.

[219] G. Zhang, S. Zhao, W. Li, Q. Du, Q. Ran, and R. Tao, "HTD-Net: A deep convolutional neural network for target detection in hyperspectral imagery," Remote Sensing, vol. 12, no. 9, May 2020.

[218] Y. Zhang, W. Li, H.-C. Li, R. Tao, and Q. Du, "Discriminative marginalized least squares regression for hyperspectral image classification," IEEE Transactions on Geoscience and Remote Sensing, vol. 58, no. 5, pp. 3148-3161, May 2020.

[217] W. Xie, J. Lei, Y. Cui, Y. Li, and Q. Du, "Hyperspectral pansharpening with deep priors," IEEE Transactions on Neural Networks and Learning Systems, vol. 31, no. 5, pp. 1529-1543, May 2020.

[216] Q. Ran, X. Xu, S. Zhao, W. Li, and Q. Du, "Remote sensing images super-resolution with deep convolution networks," Multimedia Tools and Applications, vol. 79, pp. 8985-9001, April 2020.

[215] Y. Xu, J. Peng, and Q. Du, "Multiple feature ideal regularized kernel for hyperspectral imagery classification," APSIPA Transactions on Signal and Information Processing, vol. 9, March 2020.

[214] Z. Li, T. Wang, W. Li, Q. Du, C. Wang, C. Liu, and X. Bin, "Deep multilayer fusion dense network for hyperspectral image classification," IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 13, pp. 1258-1270, 2020.

[213] K. Ren, W. Sun, X. Meng, G. Yang, and Q. Du, "Fusing China GF-5 hyperspectral data with GF-1, GF-2 and Sentinel-2A multispectral data: Which methods should be used?" Remote Sensing, vol. 12, no. 5, March 2020.

[212] S. Liu, Q. Hu, X. Tong, J. Xia, Q. Du, A. Samat, and X. Ma, "A multi-scale superpixel-guided filter feature extraction and selection approach for classification of very-high-resolution remotely sensed imagery," Remote Sensing, vol. 12, no. 5, March 2020.

[211] S. Huang, H. Zhang, Q. Du, and A. Pizurica, "Sketch-based subspace clustering of hyperspectral images," Remote Sensing, vol. 12, no. 5, March 2020.

[210] W. Xie, J. Lei, J. Yang, Y. Li, Q. Du, and Z. Li, "Deep latent spectral representation learning-based hyperspectral band selection for target detection," IEEE Transactions on Geoscience and Remote Sensing, vol. 53, no. 3, pp. 2015-2026, March 2020.

[209] Y.-J. Deng, H.-C. Li, X. Song, Y. Sun, X. Zhang, and Q. Du, "Patch tensor-based multi-graph embedding framework for dimensionality reduction of hyperspectral images," IEEE Transactions on Geoscience and Remote Sensing, vol. 53, no. 3, pp. 1630-1643, March 2020.

[208] W. Sun, J. Peng, G. Yang, and Q. Du, "Correntropy-based sparse spectral clustering for hyperspectral band selection," IEEE Geoscience and Remote Sensing Letters, vol. 17, no. 3, pp. 484-488, March 2020.

[207] J. Qu, Y. Li, Q. Du, and H. Xia, "Hyperspectral and panchromatic image fusion via adaptive tensor and multi-scale Retinex algorithm," IEEE Access, vol. 8, pp. 30522-30532, 2020.

[206] H.-C. Li, W.-Y. Wang, L. Pan, W. Li, Q. Du, and R. Tao, "Robust capsule network based on maximum correntropy criterion for hyperspectral image classification," IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 13, pp. 738-751, 2020.

[205] H.-C. Li, G. Yang, W. Yang, Q. Du, and W. Emery, "Deep nonsmooth nonnegative matrix factorization network with semi-supervised learning for SAR image change detection," ISPRS Journal of Photogrammetry and Remote Sensing, vol. 160, pp. 167-179, February 2020.

[204] W. Xie, J. Yang, J. Lei, Y. Li, and Q. Du, "SRUN:  Spectral regularized unsupervised networks for hyperspectral target detection," IEEE Transactions on Geoscience and Remote Sensing, vol. 58, no. 2, pp. 1463-1474, February 2020.

[203] W. Sun, G. Yang, J. Peng, and Q. Du, "Lateral-slice sparse tensor robust principal component analysis for hyperspectral image classification," IEEE Geoscience and Remote Sensing Letters, vol. 17, no. 1, pp. 107-111, January 2020.

[202] G. Li, Y. Xu, Y. Zhao, Q. Du, and Y. Huang, "Evaluating convolutional neural networks for cage-free floor egg detection," Sensors, January 2020.

[201] K. Tan, H. Wang, L. Chen, Q. Du, P. Du, and C. Pan, "Estimation of the spatial distribution of heavy metals in agricultural soils using airborne hyperspectral imaging and random forest," Journal of Hazardous Materials, vol. 382, January 2020.

[200] M. Zhang, W. Li, Q. Du, L. Gao, and B. Zhang, "Feature extraction for classification of hyperspectral and LiDAR data using patch-to-patch CNN," IEEE Transactions on Cybernetics, vol. 50, no. 1, pp. 100-111, January 2020.

[199] J. Li, R. Cui, B. Li, R. Song, Y. Li, and Q. Du, "Hyperspectral image super-resolution with 1D-2D attentional convolutional neural network,” Remote Sensing, vo. 11, no. 23, 2859, December 2019.

[198] X. Shi, C. Zhu, X. Ding, Q. Du, N. H. Younan, and L. Li, "A superpixel-based coastline extraction algorithm for single-polarized ENVISAT and ERS imagery," IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 12, no. 12, pp. 5118-5133, December 2019.

[197] W. Li, Z. Wang, L. Li, and Q. Du, "Feature extraction for hyperspectral images using local contain profile," IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 12, no. 12, pp. 5035-5046, December 2019.

[196] W. Yang, J. Peng, W. Sun, and Q. Du, "Log-Euclidean kernel based joint sparse representation for hyperspectral image classification," IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 12, no. 12, pp. 5023-5034, December 2019.

[195] R. Tao, X. Zhao, W. Li, H.-C. Li, and Q. Du, "Hyperspectral anomaly detection by fractional Fourier entropy," IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 12, no. 12, pp. 4920-4929, December 2019.

[194] Y. Xu, Q. Du, W. Li, and N. H. Younan, "Efficient probabilistic collaborative representation based classifier for hyperspectral image classification," IEEE Geoscience and Remote Sensing Letters, vol. 16, no. 11, pp. 1746-1750, November 2019.

[193] X. Tong, Z. Ye, Y. Xu, S. Gao, K. Luan, H. Xie, Q. Du, S. Liu, X. Xu, S. Liu, and S. Uwe, "Image registration with Fourier-based image correlation: A comprehensive review of developments and applications," IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 12, no. 10, pp. 4062-4081, October 2019.

[192] K. Li, W. Xie, Q. Du, and Y. Li, "DDLPS: Detailed-based deep Laplacian pansharpening for hyperspectral imagery," IEEE Transactions on Geoscience and Remote Sensing, vol. 57, no. 10, pp. 8011-8025, October 2019.

[191] J. Li, Y. Li, R. Song, S. Mei, and Q. Du, "Local spectral similarity regularized robust sparse hyperspectral unmixing," IEEE Transactions on Geoscience and Remote Sensing, vol. 57, no. 10, pp. 7756-7769, October 2019.

[190] L. Ma, C. Luo, J. Peng, and Q. Du, "Unsupervised manifold alignment for cross-domain classification of remote sensing images," IEEE Geoscience and Remote Sensing Letters, vol. 16, no. 10, pp. 1650-1654, October 2019.

[189] W. Sun, G. Yang, J. Peng, and Q. Du, "Hyperspectral band selection using weighted kernel regularization," IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 12, no. 9, pp. 3665-3676, September 2019.

[188] S. Liu, Q. Du, X. Tong, A. Samat, and L. Bruzzone, "Unsupervised change detection in multispectral remote sensing images via spectral-spatial band expansion," IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 12, no. 9, pp. 3578-3687, September 2019.

[187] W. Li, Y. Zhang, N. Liu, Q. Du, and R. Tao, "Structure-aware collaborative representation for hyperspectral image classification," IEEE Transactions on Geoscience and Remote Sensing, vol. 57, no. 9, pp. 7246-7261, September 2019.

[186] Y. Wang, K. Tan, Q. Du, Y. Chen, and P. Du, "Caps-TripleGAN: GAN-assisted CapsNet for hyperspectral image classification," IEEE Transactions on Geoscience and Remote Sensing, vol. 57, no. 9, pp. 7232-7245, September 2019.

[185] S. Mei, J. Ji, Y. Geng, Z. Zhang, X. Li, and Q. Du, "Unsupervised spatial-spectral feature learning by 3-dimensional convolutional autoencoder for hyperspectral classification," IEEE Transactions on Geoscience and Remote Sensing, vol. 57, no. 9, pp. 6808-6820, September 2019.

[184] K. Tan, Z. Hou, D. Ma, Y. Chen, and Q. Du, "Anomaly detection in hyperspectral imagery based on low rank representation incorporating a spatial constraint," vol. 11, no. 13, Remote Sensing, July 2019.

[183] Z. Hua, W. Sun, G. Yang, and Q. Du, "A full-coverage daily average PM2.5 retrieval method with two-stage IVW fused MODIS C6 AOD and two-stage GAM model," Remote Sensing, vol. 11, no. 13, July 2019.

[182] K. Tan, W. Ma, F. Wu, and Q. Du, "Random forest-based estimation of heavy metal concentration in agricultural soils with hyperspectral sensor data," Environmental Monitoring and Assessment, vol. 191, pp. 433-446, July 2019.

[181] C. Ge, Q. Du, W. Li, Y. Li, and W. Sun, "Hyperspectral and LiDAR data classification using kernel collaborative representation based residual fusion," IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 12, no. 6, pp. 1963-1973, June 2019.

[180] W. Sun and Q. Du, "Hyperspectral band selection: A review," IEEE Geoscience and Remote Sensing Magazine, vol. 7, no. 2, pp. 118-139, June 2019.

[179] J. Peng, W. Sun, L. Ma, and Q. Du, "Discriminative transfer joint matching for domain adaptation in hyperspectral image classification," IEEE Geoscience and Remote Sensing Letters, vol. 16, no. 6, pp. 972-974, June 2019.

[178] K. Tan, Z. Hou, F. Wu, Q. Du, and Y. Chen, "Anomaly detection for hyperspectral images based on regularized subspace method and collaborative representation," Remote Sensing, vol. 11, no 11, June 2019.

[177] J. Qu, Y. Li, Q. Du, W. Dong, and B. Xi, "Hyperspectral pansharpening based on homomorphic filtering and weighted tensor matrix," Remote Sensing, vol. 11, no. 9, May 2019.

[176] W. Li, C. Chen, M. Zhang, H.-C. Li, and Q. Du, "Data augmentation for hyperspectral image classification with deep CNN," IEEE Geoscience and Remote Sensing Letters, vo. 16, no. 4, pp. 593-597, April 2019.

[175] D. Ou, K. Tan, Q. Du, J. Zhu, X. Wang, and Y. Chen, "A novel tri-training technique for semi-supervised classification of hyperspectral images based on regularized local discriminant embedding," Remote Sensing, vol. 11, no. 6, March 2019.

[174] C. Ge, Y. Li, W. Su, J. Peng, K. Wang, and Q. Du, "Hyperspectral and LiDAR data fusion classification using superpixel segmentation based local pixel neighborhood preserving embedding," Remote Sensing, vol. 11, no. 5, March 2019.

[173] S. Yang, J. Hou, Y. Jia, S. Mei, and Q. Du, "Pseudo-label guided kernel learning for hyperspectral image classification," IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 12, no. 3, pp. 1000-1011, March 2019.

[172] H. Liu, P. Sun, Q. Du, Z. Wu, and Z. Wei, "Hyperspectral image restoration based on low-rank recovery with a local neighborhood weighted spectral-spatial total variation," IEEE Transactions on Geoscience and Remote Sensing , vol. 57, no. 3, pp. 1409-1422, March 2019.

[171] K. Tan, F. Wu, Q. Du, and P. Du, "A parallel Gaussian-Bernoulli restricted Boltzmann machine for mining area classification with hyperspectral imagery," IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 12, no. 2, pp. 627-636, February 2019.

[170] H. Su, B. Zhao, Q. Du, and P. Du, "Kernel collaborative representation with local correlation features for hyperspectral image classification," IEEE Transactions on Geoscience and Remote Sensing, vol. 57, no. 2, pp. 1230-1241, February 2019.

[169] J. Peng, W. Sun, and Q. Du, "Self-paced joint sparse representation for the classification of hyperspectral images," IEEE Transactions on Geoscience and Remote Sensing, vol. 57, no. 2, pp. 1183-1194, February 2019.

[168] J. Yin, C. Huang, X. Luo, and Q. Du, "Automatic endmember bundle unmixing methodology for lunar regional area mineral mapping," Icarus, vol. 319, pp. 349-362, February 2019.

[167] Q. Wang, Z. Yuan, Q. Du, and X. Li, "GETNET: A general end-to-end two-dimensional CNN framework for hyperspectral image change detection," IEEE Transactions on Geoscience and Remote Sensing, vol. 57, no. 1, pp. 3-13, January 2019.

[166] H. Su, Z. Wu, Q. Du, and P. Du, "Hyperspectral anomaly detection using collaborative representation with outlier removal," IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 11, no. 12, pp. 5029-5038, December 2018.

[165] N. Liu, W. Li, and Q. Du, "Unsupervised feature extraction for hyperspectral imagery using collaboration-competition graph," IEEE Journal of Selected Topics in Signal Processing, vol. 12, no. 6, pp. 1491-1503, December 2018.

[164] J. Li, B. Xi, Q. Du, R. Song, Y. Li, and G. Ren, "Deep kernel extreme-learning machine for the spectral-spatial classification of hyperspectral imagery," Remote Sensing, vol. 10, no. 12, December 2018.

[163] Y.-J. Deng, H.-C. Li, K. Fu, Q. Du, and W. Emery, "Tensor low rank discriminant embedding for hyperspectral image dimensionality reduction," IEEE Transactions on Geoscience and Remote Sensing, vol. 56, no. 12, pp. 7183-7194, December 2018.

[162] K. Tan, Q. Du, P. Du, and J. Xiao, "Change detection based on stacked generalization system with segmentation constraint," Photogrammetric Engineering & Remote Sensing, vol. 84, no, 11, pp. 733-741, November 2018.

[161] L. Pan, H.-C. Li, J. Ni, C. Chen, X.-Dong Chen, Q. Du, "GPU-based fast hyperspectral image classification using joint sparse representation with sparse consistency constraint," Journal of Real-Time Image Processing, vol. 15, no. 3, pp. 463-475, October 2018.

[160] X.-R. Feng, H.-C. Li, J. Li, Q. Du, A. Plaza, and W. Emery, "Hyperspectral unmixing using sparsity constrained deep nonnegative matrix factorization with total variation," IEEE Transactions on Geoscience and Remote Sensing, vol. 57, no. 10, pp. 6245-6257, October 2018.

[159] Y.-J. Deng, H.-C. Li, Q. Wang, and Q. Du, "Nuclear norm-based matrix regression preserving embedding for face recognition," Neurocomputing, vol. 311, pp. 279-290, October 2018.

[158] L. Pan, H.-C. Li, Y.-J. Sun, and Q. Du, "Hyperspectral image reconstruction using latent low-rank representation for classification," IEEE Geoscience and Remote Sensing Letters, vol. 15, no. 9, pp. 1422-1426, September 2018.

[157] D. Ou, K. Tan, Q. Du, Y. Chen, and J. Ding, "Decision fusion of D-InDAR and pixel offset tracking for coal mining deformation monitoring," Remote Sensing, vol. 10, no. 7, July 2018.

[156] J. Li, Q. Du, W. Li, and Y. Li, "Hyperspectral image classification with imbalanced data based on orthogonal complement subspace projection," IEEE Transactions on Geoscience and Remote Sensing vol. 57, no. 7, pp. 3838-3851, July 2018.

[155] W. Sun and Q. Du, "Graph-regularized fast and robust principal component analysis for hyperspectral band selection," IEEE Transactions on Geoscience and Remote Sensing, vol. 56, no. 6, pp. 3185-3195, June 2018.

[154] M. Zhang, W. Li, and Q. Du, "Diverse region-based CNN for hyperspectral image classification," IEEE Transactions on Image Processing, vol. 27, no. 6, pp. 2623-2634, June 2018.

[153] Q. Ran, W. Li, and Q. Du, "Kernel one-class weighted sparse representation for change detection," Remote Sensing Letters, vol. 9, no. 6, pp. 597-606, June 2018.

[152] L. Pan, H.-C. Li, and Q. Du, "Gabor feature-based composite kernel method for hyperspectral image classification," Electronics Letters, vol. 54, no. 10, pp. 628-630, May 2018.

[151] S. Mei, J. Hou, J. Chen, L.-P. Chau, and Q. Du, "Simultaneous spatial and spectral low-rank representation of hyperspectral images for classification," IEEE Transactions on Geoscience and Remote Sensing, vol. 56, no. 5, pp. 2872-2886, May 2018.

[150] H. Xie, A. Zhao, S. Huang, J. Han, S. Liu, X. Luo, H. Pan, Q. Du, X. Tong, "Unsupervised hyperspectral remote sensing image clustering based on adaptive density," IEEE Geoscience and Remote Sensing Letters, vol. 15, no. 4, pp. 632-636, April 2018.

[149] H. Su, B. Zhao, Q. Du, P. Du, and Z. Xue, "Multi-feature learning for collaborative representation classification of hyperspectral imagery," IEEE Transactions on Geoscience and Remote Sensing, vol. 56, no. 4, pp. 2467-2484, April 2018.

[148] W. Li, F. Feng, H.-C. Li, and Q. Du, "Survey on Discriminant Analysis-based Dimension Reduction for Hyperspectral Image Classification," IEEE Geoscience and Remote Sensing Magazine, vol. 6, no. 1, pp. 15-34, March 2018.

[147] W. Sun, L. Tian, Y. Xu, B. Du, and Q. Du, "A randomized subspace learning based anomaly detector for hyperspectral imagery," Remote Sensing, vol. 10, no. 3, March 2018.

[146] J. Li, B. Xi, Y. Li, Q. Du, and K. Wang, "Hyperspectral classification based on texture feature enhancement and deep belief networks," Remote Sensing, vol. 10, no. 3, March 2018.

[145] X. Xu, W. Li, Q. Ran, Q. Du, L. Gao, and B. Zhang, "Multi-source remote sensing data classification based on convolutional neural network," IEEE Transactions on Geoscience and Remote Sensing, vol. 56, no. 2, pp. 937-949, February 2018.

[144] J. Li, X. Zhao, Y. Li, Q. Du, and J. Hu, "Classification of hyperspectral imagery using a new fully convolutional neural network," IEEE Geoscience and Remote Sensing Letters, vol. 15, no. 2, pp. 291-296, February 2018.

[143] Y.-J. Deng, H.-C. Li, L. Pan, L.-Y. Shao, Q. Du, and W. Emery, "Modified tensor locality preserving projection for dimensionality reduction of hyperspectral images," IEEE Geoscience and Remote Sensing Letters, vol. 15, no. 2, pp. 277-281, February 2018.

[142] B. Du, Y. Su, S. Cai, C. Wu, and Q. Du, "Object tracking in satellite videos by fusing the kernel correlation filter and the three-frame-difference algorithm," IEEE Geoscience and Remote Sensing Letters, vol. 15, no. 2, pp. 168-172, February 2018.

[141] K. Wu, Q. Du, X. Hu, and X. Wang, "Sub-pixel mapping based on MAP model and spatial attraction theory for remotely sensed image," IEEE Access, vol. 5, December 2017.

[140] J. Peng and Q. Du, "Robust joint sparse representation based on maximum correntropy criterion for hyperspectral image classification," IEEE Transactions on Geoscience and Remote Sensing, vol. 55, no. 12, pp. 7152-7164, December 2017.

[139] W. Sun, L. Tian, Y. Xu, and Q. Du, "Fast and robust self-representation method for hyperspectral band selection," IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 10, no. 11, pp. 5087-5098, November 2017.

[138] S. Mei, X. Yuan, J. Ji, Y. Zhang, S. Wan, and Q. Du, "Hyperspectral image spatial super-resolution via 3D full convolutional neural network," Remote Sensing, vol. 9, no. 11, November 2017.

[137] L. Pan, H.-C. Li, H. Meng, W. Li, Q. Du, and W. Emery, "Hyperspectral image classification using low-rank and sparse representation with spectral consistency constraint," IEEE Geoscience and Remote Sensing Letters, vol. 14, no. 11, pp. 2117-2121, November 2017.

[136] L. Pan, H.-C. Li, W. Li, X.-D. Chen, G.-N. Wu, and Q. Du, "Discriminant analysis of hyperspectral imagery using fast kernel sparse and low-rank graph," IEEE Transactions on Geoscience and Remote Sensing, vol. 55, no. 11, pp. 6085-6098, November 2017.

[135] S. Liu, Q. Du, X. Tong, A. Samat, H. Pan, and X. Ma, "Band selection based dimensionality reduction for change detection in multitemporal hyperspectral images," Remote Sensing, vol. 9, no. 10, October 2017.

[134] M. Zhang, W. Li, and Q. Du, "Collaborative classification of hyperspectral and visible images with convolutional neural network and decision fusion," Journal of Applied Remote Sensing, vol. 11, no. 4, October 2017.

[133] S. Liu, Q. Du, X. Tong, A. Samat, L. Bruzzone, and F. Bovolo, "Multiscale morphological compressed change vector analysis for unsupervised multiple change detection," IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing , vol. 10, no. 9, pp. 4124-4137, September 2017.

[132] H. Yu, L. Gao, W. Li, Q. Du, and B. Zhang, "Locality sensitive discriminant analysis for group sparse representation-based hyperspectral image classification," IEEE Geoscience and Remote Sensing Letters, vol. 14, no. 8, pp. 1358-1362, August 2017.

[131] S. Mei, J. Ji, J. Hou, X. Li, and Q. Du, "Learning sensor-specific spatial-spectral features of hyperspectral images via convolutional neural networks," IEEE Transactions on Geoscience and Remote Sensing, vol. 55, no. 8, pp. 4520-4533, August 2017.

[130] Y. Xu, Q. Du, W. Li, C. Chen, and N. H. Younan, "Nonlinear classification of multispectral imagery with representation-based classifiers," Remote Sensing, vol. 9, no. 7, July 2017.

[129] S. Mei, Q. Bi, J. Ji, and Q. Du, "Hyperspectral image classification by exploring low-rank property in spectral-spatial domain," IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 10, no. 6, pp. 2910-2921, June 2017.

[128] X. Bian, C. Chen, L. Tian, and Q. Du, "Fusing local and global features for high-resolution scene classification," IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 10, no. 6, pp. 2886-2901, June 2017.

[127] K. Wu and Q. Du, "Sub-pixel change detection of multi-temporal remote sensed images using variability of endmembers," IEEE Geoscience and Remote Sensing Letters, vol. 14, no. 6, pp. 796-800, June 2017.

[126] L. Pan, H. Li, Y. Deng, F. Zhang, X. Chen, and Q. Du, "Hyperspectral dimensionality reduction by tensor sparse and low-rank graph-based discriminant analysis," Remote Sensing, vol. 9, no. 5, May 2017.

[125] W. Li, G. Wu, and Q. Du, "Transferred deep learning for anomaly detection in hyperspectral imagery," IEEE Geoscience and Remote Sensing Letters, vol. 14, no. 5, pp. 597-601, May 2017.

[124] F. Feng, W. Li, Q. Du, and B. Zhang, "Dimensionality reduction of hyperspectral image with graph-based discriminant analysis considering spectral similarity," Remote Sensing, vol. 9, no. 4, April 2017.

[123] Y. Xu, Q. Du, and N. H. Younan, "Particle swarm optimization-based band selection for hyperspectral target detection," IEEE Geoscience and Remote Sensing Letters, vol. 14, no. 3, pp. 554-558, April 2017.

[122] K. Wu, Q. Du, Y. Wang, and Y. Yang, "Supervised sub-pixel mapping for change detection from remotely sensed images with different spatial resolutions," Remote Sensing, vol. 9, no. 3, March 2017.

[121] V. Menon, Q. Du, and J. E. Fowler, "Random Hadamard projections for hyperspectral unmixing," IEEE Geoscience and Remote Sensing Letters, vol. 14, no. 3, pp. 419-423, March 2017.

[120] W. Li, G. Wu, F. Zhang, and Q. Du, "Hyperspectral image classification with deep pixel-pair features," IEEE Transactions on Geoscience and Remote Sensing, vol. 55, no. 2, pp. 844-853, February 2017.

[119] H. Su, Y. Cai, and Q. Du, "Firefly-algorithm-inspired framework with band selection and extreme learning machine for hyperspectral image classification," IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 10, no. 1, pp. 309-320, January 2017.

[118] X. Bian, C. Chen, Y. Xu, and Q. Du, "Robust hyperspectral image classification by multi-layer spatial-spectral sparse representations," Remote Sensing, vol. 8, no. 12, December 2016.

[117] W. Li and Q. Du, "Laplacian regularized collaborative graph for discriminant analysis of hyperspectral imagery," IEEE Transactions on Geoscience and Remote Sensing, vol. 54, no. 12, pp. 7066-7076, December 2016.

[116] J. Li, Q. Du, and Y. Li, "An efficient radial basis function neural network for hyperspectral remote sensing image classification," Soft Computing, vol. 20, no. 12, pp. 4753-4759, December 2016.

[115] W. Li and Q. Du, "A survey on representation-based classification and detection in hyperspectral imagery," Pattern Recognition Letters, vol. 83, pp. 115-123, November 2016.

[114] Q. Ran, M. Zhang, W. Li, and Q. Du, "Change detection with one-class sparse representation classifier," Journal of Applied Remote Sensing, vol. 10, no. 4, October 2016.

[113] A. Sumarsono and Q. Du, "Low-rank subspace representation for supervised and unsupervised classification of hyperspectral image classification," IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 9, no. 9, pp. 4188-4195, September 2016.

[112] W. Li, Q. Du, F. Zhang, and W. Hu, "Hyperspectral image classification by fusing collaborative and sparse representations," IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 9, no. 9, pp. 4178-4187, September 2016.

[111] K. Tan, J. Zhu, Q. Du, L. Wu, P. Du, "A novel tri-training technique for semi-supervised classification of hyperspectral images based on diversity measurement," Remote Sensing, vol. 8, no. 9, September 2016.

[110] V. Menon, Q. Du, and J. E. Fowler, "Fast SVD with random Hadamard projection for hyperspectral dimensionality reduction," IEEE Geoscience and Remote Sensing Letters, vol. 13, no. 9, pp. 1275-1279, September 2016.

[109] H. Su, B. Zhao, Q. Du, and Y. Sheng, "Tangent distance-based collaborative representation for hyperspectral image classification," IEEE Geoscience and Remote Sensing Letters, vol. 13, no. 9, pp. 1236-1240, September 2016.

[108] K. Wu, D. Zhao, Y. Zhong, and Q. Du, "Multi-probe based artificial DNA encoding and matching classifier for hyperspectral remote sensing imagery," Remote Sensing, vol. 8, no. 8, August 2016.

[107] W. Li, J. Liu, and Q. Du, "Sparse and low-rank graph for discriminant analysis of hyperspectral imagery," IEEE Transactions on Geoscience and Remote Sensing, vol. 54, no. 7, pp. 4094-4105, July 2016.

[106] J. Zou, W. Li, C. Chen, and Q. Du, "Scene classification using local and global features with collaborative representation fusion," Information Sciences, vol. 348, pp. 209-226, June 2016.

[105] L. Huang, C. Chen, W. Li, and Q. Du, "Remote sensing scene classification using multi-scale completed local binary patterns and Fisher vectors," Remote Sensing, vol. 8, no. 6, June 2016.

[104] S. Mei, Q. Bi, J. Ji, J. Hou, and Q. Du, "Spectral variation alleviation by low-rank matrix approximation for hyperspectral image analysis," IEEE Geoscience and Remote Sensing Letters, vol. 13, no. 5, pp. 796-800, May 2016.

[103] H. Su, B. Yong, and Q. Du, "Hyperspectral band selection using improved firefly algorithm," IEEE Geoscience and Remote Sensing Letters, vol. 13, no. 1, pp. 68-72, January 2016.

[102] J. Zou, W. Li, and Q. Du, "Sparse representation-based nearest neighbor classifiers for hyperspectral imagery," IEEE Geoscience and Remote Sensing Letters, vol. 12, no. 12, pp. 2418-2422, Dec. 2015.

[101] J. Li, M. Guo, H. Zhang, L. Zhang, H. Shen, and Q. Du, "Urban classification by fusing thermal hyperspectral and visible data," Photogrammetric Engineering & Remote Sensing, vol. 81, no. 12, pp. 901-911, Dec. 2015.

[100] W. Li, Q. Du, and B. Zhang, "Combined sparse and collaborative representation for hyperspectral target detection," Pattern Recognition, vol. 48, no. 12, pp. 3904-3916, Dec. 2015.

[99] B. Peng, W. Li, X. Xie, Q. Du, and K. Liu, "Weighted-fusion-based representation classifiers for hyperspectral imagery," Remote Sensing, vol. 7, 14806-14826, Nov. 2015.

[98] A. Sumarsono and Q. Du, "Low-rank subspace representation for estimating the number of signal subspaces in hyperspectral imagery," IEEE Transactions on Geoscience and Remote Sensing, vol. 53, no. 11, pp. 6286-6292, Nov. 2015.

[97] K. Tan, J. Zhang, Q. Du, and X. Wang, "GPU parallel implementation of support vector machines for hyperspectral image classification," IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 8, no. 10, pp. 4647-4656, Oct. 2015.

[96] K. Tan, S. Zhou, and Q. Du, "Semi-supervised discriminant analysis for hyperspectral imagery with block-sparse graph," IEEE Geoscience and Remote Sensing Letters, vol. 12, no. 8, pp. 1765-1769, Aug. 2015.

[95] W. Li, C. Chen, H. Su, and Q. Du, "Local binary patterns and extreme learning machine for hyperspectral imagery classification," IEEE Transactions on Geoscience and Remote Sensing, vol. 53, no. 7, pp. 3681-3693, July 2015.

[94] S. Mei, Q. Du, and M. He, "Equivalent-sparse unmixing through spatial and spectral constrained endmember selection from an image-derived spectral library," IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing vol. 8, no. 6, pp. 2665-2675, June 2015.

[93] L. Gao, B. Yang, Q. Du, and B. Zhang, "Adjusted spectral matched filter for target detection in hyperspectral imagery," Remote Sensing, vol. 7, no. 6, pp. 6611-6634, June 2015.

[92] M. Xiong, Q. Ran, W. Li, J. Zou, and Q. Du, "Hyperspectral image classification using weighted joint collaborative representation," IEEE Geoscience and Remote Sensing Letters , vol. 12, no. 6, pp. 1209-1213, June 2015.

[91] D. Han, Q. Du, J. V. Aanstoos, and N. H. Younan, "Classification of levee slides from airborne synthetic aperture radar images with efficient spatial feature extraction," Journal of Applied Remote Sensing, vol. 9, March 2015.

[90] Q. Ran, W. Li, Q. Du, and C. Yang, "Hyperspectral image classification for mapping agricultural tillage practices," Journal of Applied Remote Sensing, vol. 9, March 2015.

[89] J. Li, Q. Du, W. Li, and Y. Li, "Optimizing extreme learning machine for hyperspectral image classification," Journal of Applied Remote Sensing, vol. 9, Mar. 2015.

[88] W. Li and Q. Du, "Collaborative representation for hyperspectral anomaly detection," IEEE Transactions on Geoscience and Remote Sensing, vol. 53, no. 3, pp. 1463-1474, Mar. 2015.

[87] W. Li and Q. Du, "Decision fusion for dual-window based hyperspectral anomaly detection," Journal of Applied Remote Sensing, vol. 9, Feb. 2015.

[86] W. Li, Q. Du, F. Zhang, and W. Hu, "Collaborative representation based nearest neighbor classifier for hyperspectral imagery," IEEE Geoscience and Remote Sensing Letters, vol. 12, no. 2, pp. 389-393, Feb. 2015.

[85] W. Li, Q. Du, and M. Xiong, "Kernel collaborative representation with Tikhonov regularization for hyperspectral image classification," IEEE Geoscience and Remote Sensing Letters, vol. 12, no. 1, pp. 48-52, Jan. 2015.

[84] Q. Du, E. Michaelsen, P. Du, L. Bruzzone, X. Tong, and U. Stilla, "Foreword to the special issue on pattern recognition in remote sensing," IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing , vol. 7, no. 12, pp. 4615-4619, Dec. 2014.

[83] B. Zhang, L. Zhuang, L. Gao, W. Luo, Q. Ran, and Q. Du, "PSO-EM: A hyperspectral unmixing algorithm based on normal compositional model," IEEE Transactions on Geoscience and Remote Sensing, vol. 52, no. 12, pp. 7782-7792, Dec. 2014.

[82] K. Tan, E. Li, Q. Du, and P. Du, "An efficient semi-supervised classification approach for hyperspectral imagery," ISPRS Journal of Photogrammetry and Remote Sensing, vol. 97, pp. 36-45, Nov. 2014.

[81] Q. Ran, W. Li, Q. Du, and M. Xiong, "Hyperspectral image classification with improved local-region filters," Journal of Applied Remote Sensing, vol. 8, no. 1, October 2014.

[80] J. Gao, Q. Du, L. Gao, X. Sun, and B. Zhang, "Ant colony optimization-based supervised and unsupervised band selection for hyperspectral urban data classification," Journal of Applied Remote Sensing, vol. 8, no. 1, August 2014.

[79] K. Tan, X. Jin, Q. Du, and P. Du, "Modified multiple endmember spectral mixture analysis for mapping impervious surfaces in urban environments," Journal of Applied Remote Sensing, vol. 8, no. 1, August 2014.

[78] J. Zou, W. Li, X. Huang, and Q. Du, "Classification of hyperspectral urban data with adaptive simultaneous orthogonal matching pursuit," Journal of Applied Remote Sensing, vol. 8, no. 1, July 2014.

[77] N. Ly, Q. Du, and J. E. Fowler, "Sparse graph-based discriminant analysis for hyperspectral imagery," IEEE Transactions on Geoscience and Remote Sensing, vol. 52, no. 7, pp. 3872-3884, July 2014.

[76] N. Ly, Q. Du, and J. E. Fowler, "Collaborative graph-based discriminant analysis for hyperspectral imagery," IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 7, no. 6, pp. 2688-2696, June 2014.

[75] H. Su, Q. Du, G. Chen, and P. Du, "Optimized hyperspectral band selection using particle swarm optimization," IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 7, no. 6, pp. 2659-2670, June 2014.

[74] H. Su, Q. Du, and P. Du, "Hyperspectral image visualization using band selection," IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 7, no. 6, pp. 2647-2658, June 2014.

[73] C. Debes, A. Merentitis, R. Heremans, J. Hahn, N. Frangiadakis, T. Kasteren, W. Liao, R. Bellens, A. Pizurica, S. Gautama, W. Philips, S. Prasad, Q. Du, and F. Pacifici, "Hyperspectral and LiDAR data fusion: Outcome of the 2013 GRSS data fusion contest," IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 7, no. 6, pp. 2405-2418, June 2014.

[72] Q. Du, N. Ly, and J. E. Fowler, "An operational approach to PCA+JPEG2000 compression of hyperspectral imagery," IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 7, no. 6, pp. 2237-2245, June 2014.

[71] W. Li and Q. Du, "Joint within-class collaborative representation for hyperspectral image classification," IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 7, no. 6, pp. 2200-2208, June 2014.

[70] W. Li and Q. Du, "Gabor-filtering based nearest regularized subspace for hyperspectral image classification," IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 7, no. 4, pp. 1012-1022, April 2014.

[69] K. Tan, E. Li, Q. Du, and P. Du, "Hyperspectral image classification using band selection and morphological profiles," IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing , vol. 7, no. 1, pp. 40-48, Jan. 2014.

[68] C. Berger, M. Voltersen, R. Eckardt, J. Eberle, T. Heyer, N. Salepci, S. Hese, C. Schmullius, J. Tao, S. Auer, R. Bamler, K. Ewald, M. Gartley, J. Jacobson, A. Buswell, Q. Du, and F. Pacifici, "Multi-modal and multi-temporal data fusion: Outcome of the 2012 GRSS data fusion contest," IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing , vol. 6, no. 3, pp. 1324-1340, Jun. 2013.

[67] L. Gao, B. Zhang, X. Sun, S. Li, Q. Du, and C. Wu, "Optimized maximum noise fraction for dimensionality reduction of Chinese HJ-1A hyperspectral data," EURASIP Journal on Advances in Signal Processing, Apr. 2013.

[66] L. Gao, Q. Du, B. Zhang, W. Yang, and Y. Wu, "A comparative study on linear regression-based noise estimation for hyperspectral imagery," IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 6, no. 2, pp. 488-498, Apr. 2013.

[65] N. Ly, Q. Du, and J. E. Fowler, "Reconstruction from random projections of hyperspectral imagery with spectral and spatial partitioning," IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 6, no. 2, pp. 466-472, Apr. 2013.

[64] Q. Du, L. Zhang, B. Zhang, X. Tong, P. Du, and J. Chanussot, "Foreword to the special issue on hyperspectral remote sensing: Theory, methods, and applications," IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 6, no. 2, pp. 459-465, Apr. 2013.

[63] Z. Long, W. Wei, A. Turlapty, Q. Du, and N. H. Younan, "Fusion of radiation and electromagnetic induction data for buried radioactive target detection and characterization," IEEE Transactions on Nuclear Science, vol. 60, no. 2, pp. 1126-1133, Apr. 2013.

[62] C. Yang, J. Everitt, Q. Du, B. Luo, and J. Chanussot, "Using high resolution airborne and satellite imagery to assess crop growth and yield variability for precision agriculture," Proceedings of the IEEE, vol. 101, no. 3, pp. 582-592, Mar. 2013.

[61] P. Du, J. Xia, Q. Du, Y. Luo, and K. Tan, "Evaluation on the spatio-temporal pattern of urban ecological security using remote sensing and GIS," International Journal of Remote Sensing, vol. 34, no. 3, pp. 848-863, Feb. 2013.

[60] A. Turlapty, Q. Du, and N. H. Younan, "A partially supervised approach for detection and classification of buried radioactive metal targets using electromagnetic induction data," IEEE Transactions on Geoscience and Remote Sensing, vol. 51, no. 1, pp. 108-121, Jan. 2013.

[59] H. Su, P. Du, and Q. Du, "Semi-supervised dimensionality reduction using orthogonal projection divergence-based clustering for hyperspectral imagery," Optical Engineering, vol. 51, no. 11, pp. 11715 (1-8), November 2012.

[58] W. Wei, Q. Du, N. Younan, "Optimized spectral transformation for detection and classification of buried radioactive materials," IEEE Transactions on Nuclear Science, vol. 59, no. 4, pp. 1702-1710, August 2012.

[57] C. Yang, J. A. Goolsby, J. H. Everitt, and Q. Du, "Applying six classifiers to airborne hyperspectral imagery for detecting Giant Reed," Geocarto International, vol. 27, no. 5, pp. 413-424, August 2012.

[56] H. Su and Q. Du, "Hyperspectral band clustering and band selection for urban land cover classification," Geocarto International, vol. 27, no. 5, pp. 395-411, August 2012.

[55] Q. Du, "A new sequential algorithm for hyperspectral endmember extraction," IEEE Geoscienece and Remote Sensing Letters, vol. 9, no. 4, pp. 695-699, July 2012.

[54] H. Yang, Q. Du, and G. Chen, "Particle swarm optimization-based hyperspectral dimensionality reduction for urban land cover classification," IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 5, no. 2, pp. 544-554, April 2012.

[53] J. M. Bioucas-Dias, A. Plaza, N. Dobigeon, M. Parente, Q. Du, P. Gader, and J. Chanussot, "Hyperspectral unmixing overview: Geometrical, statistical and sparse regression-based approaches," IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing , vol. 5, no. 2, pp. 354-379, April 2012.

[52] K. Liu, B. Ma, Q. Du, and G. Chen, "Fast motion detection from airborne videos using graphics processing units," Journal of Applied Remote Sensing, vol. 6, 2012.

[51] W. Wei, Q. Du, and N. Younan, "Fast supervised hyperspectral band selection using graphics processing units," Journal of Applied Remote Sensing, vol. 6, 2012.

[50] F. Pacifici and Q. Du, "Foreword to the special issue on optical multiangular data exploitation and outcome of 2011 GRSS data fusion contest," IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 5, no. 1, pp. 1-7, February 2012.

[49] A. Turlapty, B. Gokaraju, Q. Du, N. H. Younan, and J. V. Aanstoos, "A hybrid approach for building extraction from spaceborne multi-angular optical imagery," IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 5, no. 1, pp. 89-100, February 2012.

[48] N. Longbotham, F. Pacifici, T. Glenn, A. Zare, M. Volpi, D. Tuia, E. Christophe, J. Michel, J. Inglada, J. Chanussot, and Q. Du, "Multi-modal change detection, application to the detection of flooded areas: Outcomes of the 2009-2010 Datat Fusion Contest," IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 5, no. 1, pp. 331-342, February 2012.

[47] J. E. Fowler and Q. Du, "Anomaly detection and reconstruction from random projections," IEEE Transactions on Image Processing, vol. 21, no. 1, pp. 184-195, January 2012.

[46] H. Su, H. Yang, Q. Du, and Y. Sheng, "Semi-supervised band clustering for dimensionality reduction of hyperspectral imagery," IEEE Geoscience and Remote Sensing Letters, vol. 8, no. 6, pp. 1135-1139, November 2011.

[45] A. Plaza, Q. Du, J. M. Bioucas-Dias, X. Jia, and F. A. Kruse, "Foreword to the special issue on spectral unmixing of remotely sensed data," IEEE Transactions on Geoscience and Remote Sensing, vol. 49, no. 11, pp. 4103-4110, November 2011.

[44] H. Yang, Q. Du, and G. Chen, "Unsupervised hyperspectral band selection using graphics processing units," IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 4, no. 3, pp. 660-668, September 2011.

[43] A. Plaza, Q. Du, Y.-L. Chang, and R. L. King, "High performance computing for hyperspectral remote sensing," IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 4, no. 3, pp. 528-544, September 2011.

[42] A. Plaza, Q. Du, Y.-L. Chang, and R. L. King, "Foreword to the special issue on high performance computing in earth observation and remote sensing," IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 4, no. 3, pp. 503-507, September 2011.

[41] W. Zhu, Q. Du, and J. E. Fowler, "Multi-temporal hyperspectral image compression," IEEE Geoscience and Remote Sensing Letters, vol. 8, no. 3, pp. 416-420, May 2011.

[40] H. Yang, Q. Du, H. Su, and Y. Sheng, "An efficient method for supervised hyperspectral band selection," IEEE Geoscience and Remote Sensing Letters, vol. 8, no.1, pp. 138-142, Jan. 2011.

[39] Q. Du, W. Wei, D. May, and N. H. Younan, "Noise-adjusted principal component analysis for buried radioactive target detection and classification," IEEE Transactions on Nuclear Science, vol. 57, no. 6, pp. 3760-3767, Dec. 2010.

[38] H. Yang, Q. Du, and B. Ma, "Decision fusion on supervised and unsupervised classifiers for hyperspectral imagery," IEEE Geoscience and Remote Sensing Letters, vol. 7, no. 4, pp. 875-879, Oct. 2010.

[37] N. Raksuntorn and Q. Du, "Nonlinear spectral mixture analysis for hyperspectral imagery in an unknown environment," IEEE Geoscience and Remote Sensing Letters, vol. 7, no. 4, pp. 836-840, Oct. 2010.

[36] S. Cai, Q. Du, R. J. Moorhead, "Feature-driven multi-layer visualization for remotely sensed hyperspectral imagery," IEEE Transactions on Geoscience and Remote Sensing, vol. 48, no. 9, pp. 3471-3481, Sep. 2010.

[35] H. Yang, B. Ma, Q. Du, and C. Yang, "Improving urban land use and land cover classification from high-spatial-resolution hyperspectral imagery using contextual information," Journal of Applied Remote Sensing, vol. 4, 041890, Aug. 2010.

[34] C. Yang, J. H. Everitt, and Q. Du, "Applying linear spectral unmixing to airborne hyperspectral imagery for mapping yield variability in grain sorghum and cotton fields," Journal of Applied Remote Sensing, vol. 4, 041887, Aug. 2010.

[33]   K. Liu, Q. Du, H. Yang, and B. Ma, "Optical flow and principal component analysis-based motion detection in outdoor videos," EURASIP Journal on Advances in Signal Processing, vol. 2010, 680623, Jul. 2010.

[32]   J. Li, Q. Du, and C. Sun, "A modified box-counting method for image fractal dimension estimation," Pattern Recognition, vol. 42, no. 11, pp. 2460-2469, Nov. 2009.

[31] Q. Du, W. Zhu, H. Yang, J. E. Fowler, "Segmented principal component analysis for parallel compression of hyperspectral imagery," IEEE Geoscience and Remote Sensing Letters, vol. 6, no. 4, pp. 713-717, Oct. 2009.

[30]  Q. Du and R. Nekovei, "Fast real-time onboard processing of hyperspectral imagery for detection and classification," Journal of Real-Time Image Processing, vol. 4, no. 3, pp. 273-286, Aug. 2009.

[29]  Q. Du and I. Kopriva, "Dependent component analysis for blind restoration of images degraded by turbulent atmosphere," Neurocomputing, vol. 72, pp. 2682-2692, June 2009.

[28] Q. Du, J. E. Fowler, and W. Zhu, "On the impact of atmospheric correction on lossy compression of multispectral and hyperspectral imagery," IEEE Transactions on Geoscience and Remote Sensing, vol. 47, no. 1, pp. 130-132, Jan. 2009.

[27] Q. Du and J. E. Fowler, "Low-complexity principal component analysis for hyperspectral image compression," International Journal of High Performance Computing Applications, vol. 22, no. 4, pp. 438-448, Nov. 2008.

[26]  Q. Du, W. Zhu, and J. E. Fowler, "Anomaly-based JPEG2000 compression of hyperspectal imagery," IEEE Geoscience and Remote Sensing Letters, vol. 5, no.4, pp. 696-700, Oct. 2008.

[25] Q. Du and H. Yang, "Similarity-based unsupervised band selection for hyperspectral image analysis," IEEE Geoscience and Remote Sensing Letters, vol. 5, no. 4, pp. 564-568, Oct. 2008.

[24]  Q. Du, N. Raksuntorn, N. H. Younan, and R. L. King, "Endmember extraction for hyperspectral imagery," Applied Optics, vol. 47, no. 28, pp. F77-F84, Oct. 2008.

[23] Q. Du, N. Raksuntorn, S. Cai, and R. J. Moorhead, "Color display for hyperspectral imagery," IEEE Transactions on Geoscience and Remote Sensing, vol. 46, no. 6, pp. 1858-1866, Jun. 2008.

[22] Q. Du, N. Raksuntorn, A. Orduyilmaz, and L. M. Bruce, "Automatic registration and mosaicking for airborne multispectral image  sequences," Photogrammetric Engineering & Remote Sensing, vol. 74, no. 2, pp.169-181, Feb. 2008.

[21] Q. Du and I. Kopriva, "Automated target detection and discrimination using constrained kurtosis maximization," IEEE Geoscience and Remote Sensing Letters, vol. 5, no. 1, pp. 38-42, Jan. 2008.

[20] Q. Du, N.-B. Chang, C.-H. Yang, and K. R. Srilakshmi, "Combination of multispectral remote sensing, variable rate technology and environmental modeling for citrus pest management," Journal of Environmental Management, vol. 86, no. 1, pp. 14-26, Jan. 2008.

[19] Q. Du, "Modified Fisher's linear discriminant analysis for hyperspectral imagery," IEEE Geoscience and Remote Sensing Letters, vol. 4, no. 4, pp. 503-507, Oct. 2007.

[18] Q. Du, N. H. Younan, R. L. King, and V. P. Shah, "On the performance evaluation of pan-sharpening techniques," IEEE Geoscience and Remote Sensing Letters, vol. 4, no. 4, pp. 518-522, Oct. 2007.

[17] S. Cai, Q. Du, and R. J. Moorhead, "Hyperspectral image visualization using double layers," IEEE Transactions on Geoscience and Remote Sensing, vol. 45, no. 10, pp. 3028-3036, Oct. 2007.

[16] Q. Du, "Unsupervised real-time constrained linear discriminant analysis to hyperspectral image classification," Pattern Recognition, vol. 40, no. 5, pp. 1510-1519, May 2007.

[15] Q. Du and J. E. Fowler, "Hyperspectral image compression using JPEG2000 and principal component analysis," IEEE Geoscience and Remote Sensing Letters, vol. 4, no. 2, pp. 201-205, Apr. 2007.

[14] H. Ren, Q. Du, J. Wang, and C.-I Chang, "Automatic target recognition for hyperspectral imagery using high-order statistics," IEEE Transactions on Aerospace and Electronic Systems, vol. 42, no. 4, pp. 1372-1385, Dec. 2006.

[13] Q. Du, I. Kopriva, and H. Szu, "Independent component analysis for hyperspectral remote sensing imagery classification," Optical Engineering, vol. 45, no. 1, pp. 017008-1:13, Jan, 2006.

[12] Q. Du and R. Nekovei, "Implementation of real-time constrained linear discriminant analysis to remote sensing image classification," Pattern Recognition, vol. 38, no. 4, pp. 459-471, Apr. 2005.

[11] Q. Du, I. Kopriva, and H. Szu, "Independent component analysis for classifying multispectral images with dimensionality limitation," International Journal of Information Acquisition, vol. 1, no. 3, pp. 201-216, Sep. 2004.

[10] Q. Du and C.-I Chang, "Linear mixture analysis-based compression for hyperspectral image analysis," IEEE Transactions on Geoscience and Remote Sensing, vol. 42, no. 4, pp. 875-891, Apr. 2004.

[9] Q. Du and C.-I Chang, "A signal-decomposed and interference-annihilated approach to hyperspectral target detection," IEEE Transactions on Geoscience and Remote Sensing, vol. 42, no. 4, pp. 892-906, Apr. 2004.

[8] C.-I Chang and Q. Du, "Estimation of number of spectrally distinct signal sources in hyperspectral imagery," IEEE Transactions on Geoscience and Remote Sensing, vol. 42, no. 3, pp. 608-619, Mar. 2004.

[7] I. Kopriva, Q. Du, and H. Szu, "Independent component analysis approach to image sharpening in the presence of atmospheric turbulence," Optics Communications, vol. 233 (1-3), pp. 1-4, Mar. 2004.

[6] Q. Du, H. Ren, and C.-I Chang, "A comparative study for orthogonal subspace projection and constrained energy minimization," IEEE Transactions on Geoscience and Remote Sensing, vol. 41, no. 6, pp. 1525-1529, Jun. 2003.

[5] Q. Du and H. Ren, "Real-time constrained linear discriminant analysis to target detection and classification in hyperspectral imagery," Pattern Recognition, vol. 36, no. 1, pp. 1-8, Jan. 2003.

[4] Q. Du and C.-I Chang , "A hidden Markov model approach to spectral analysis for hyperspectral imagery," Optical Engineering, vol. 40, no. 10, pp. 2277-2284, Oct. 2001.

[3] Q. Du and C.-I Chang, "Linear constrained distance-based discriminant analysis for hyperspectral image classification," Pattern Recognition, vol. 34, no. 2, pp. 361-373, Feb. 2001.

[2] C.-I Chang and Q. Du, T.-L. Sun, and M. L. G. Althouse, "A joint band prioritization and band decorrelation approach to band selection for hyperspectral image classification," IEEE Transactions on Geoscience and Remote Sensing, vol. 37, no. 6, pp. 2631-2641, Nov. 1999.

[1] C.-I Chang and Q. Du, "Interference and noise adjusted principal components analysis," IEEE Transactions on Geoscience and Remote Sensing, vol. 37, no. 5, pp. 2387-2396, Sep. 1999.