期刊论文

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  • Tong, Lyuyang, et al. "An Improved Multiobjective Discrete Particle Swarm Optimization for Hyperspectral Endmember Extraction". IEEE Transactions on Geoscience and Remote Sensing (2019).
  • Zhu, Dehui, Bo Du, and Liangpei Zhang. "Binary-Class Collaborative Representation for Target Detection in Hyperspectral Images." IEEE Geoscience and Remote Sensing Letters (2019).
  • Zhu, Dehui, Bo Du, and Liangpei Zhang. "Target Dictionary Construction-Based Sparse Representation Hyperspectral Target Detection Methods." IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (2019).
  • Zhang, Lefei, et al. "Nonlocal Low-Rank Tensor Completion for Visual Data." IEEE transactions on cybernetics (2019).
  • Zhang, Lefei, et al. "Hyperspectral image unsupervised classification by robust manifold matrix factorization." Information Sciences 485 (2019): 154-169.
  • Du, Bo, et al. "Object Tracking in Satellite Videos Based on a Multi-Frame Optical Flow Tracker." arXiv preprint arXiv:1804.09323 (2018).
  • Xu, Yonghao, et al. "Advanced Multi-Sensor Optical Remote Sensing for Urban Land Use and Land Cover Classification: Outcome of the 2018 IEEE GRSS Data Fusion Contest." IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (2019).
  • Xu, Yonghao, Bo Du, and Liangpei Zhang. "Beyond the Patchwise Classification: Spectral-Spatial Fully Convolutional Networks for Hyperpsectral Image Classificaiton." IEEE Transactions on Big Data (2019).
  • Wang, Zengmao, , et al. "Incorporating Distribution Matching into Uncertainty for Multiple Kernel Active Learning." IEEE Transactions on Knowledge and Data Engineering (2019).
  • Wang, Zengmao, et al. "Domain Adaptation With Discriminative Distribution and Manifold Embedding for Hyperspectral Image Classification." IEEE Geoscience and Remote Sensing Letters (2019).
  • Liu, Weiwei, et al. "Hyperspectral Imagery Classification via Stochastic HHSVMs." IEEE Transactions on Image Processing 28.2 (2018): 577-588.
  • Wang, Ziye, Yanni Dong, and Renguang Zuo. "Mapping geochemical anomalies related to Fe–polymetallic mineralization using the maximum margin metric learning method." Ore Geology Reviews 107 (2019): 258-265.
  • Wang, Ziye, Renguang Zuo, and Yanni Dong. "Mapping Geochemical Anomalies Through Integrating Random Forest and Metric Learning Methods." Natural Resources Research (2019): 1-14.
  • Zhang, Yuxiang, et al. "Multitask Learning-Based Reliability Analysis for Hyperspectral Target Detection." IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (2019).
  • Cheng, Qian, et al. "ANSGA-III: A Multiobjective Endmember Extraction Algorithm for Hyperspectral Images." IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (2019).
  • Du, Bo, Qiuci Wei, and Rong Liu. "An Improved Quantum-Behaved Particle Swarm Optimization for Endmember Extraction." IEEE Transactions on Geoscience and Remote Sensing (2019).
  • Li, Xue, et al. "Iterative Privileged Learning." IEEE transactions on neural networks and learning systems (2019).
  • Xu, Mingming, Bo Du, and Yanguo Fan. "Endmember Extraction From Highly Mixed Data Using Linear Mixture Model Constrained Particle Swarm Optimization." IEEE Transactions on Geoscience and Remote Sensing (2019).
  • Chenhong, Ruixuan, et al. "Deep Siamese Multi-scale Convolutional Network for Change Detection in Multi-temporal VHR Images." IEEE Transactions on Image Processing (2019).
  • Shao, Jia, Bo Du, Chen Wu. "Can We Track Targets from the Space? A Hybrid Kernel Correlation Filter Tracker for Satellite Video." IEEE Transactions on Geoscience and Remote Sensing (2019).
  • Shao, Jia, Bo Du, Chen Wu. "Tracking Objects From Satellite Videos: A Velocity Feature Based Correlation Filter". IEEE Transactions on Geoscience and Remote Sensing (2019).
  • Chang, Shizhen, Bo Du, and Liangpei Zhang. "BASO: A background-anomaly component projection and separation optimized filter for anomaly detection in hyperspectral images." IEEE Transactions on Geoscience and Remote Sensing 56.7 (2018): 3747-3761.
  • Dong, Yanni, et al. "Hyperspectral Target Detection via Adaptive Information—Theoretic Metric Learning with Local Constraints." Remote Sensing 10.9 (2018): 1415.
  • Du, Bo, et al. "Object Tracking in Satellite Videos Based on a Multi-Frame Optical Flow Tracker." arXiv preprint arXiv:1804.09323 (2018).
  • Du, Bo, Zhiqiang Huang, and Nan Wang. "A Bandwise Noise Model Combined With Low-Rank Matrix Factorization for Hyperspectral Image Denoising." IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 11.4 (2018): 1070-1081.
  • Du, Bo, et al. "Joint weighted nuclear norm and total variation regularization for hyperspectral image denoising." International journal of remote sensing 39.2 (2018): 334-355.
  • Du, Bo, et al. "Unsupervised Deep Slow Feature Analysis for Change Detection in Multi-Temporal Remote Sensing Images." arXiv preprint arXiv:1812.00645 (2018).
  • Du, Bo, et al. "Object Tracking in Satellite Videos by Fusing the Kernel Correlation Filter and the Three-Frame-Difference Algorithm." IEEE Geoscience and Remote Sensing Letters 15.2 (2018): 168-172.
  • Du, Bo, et al. "Robust graph-based semisupervised learning for noisy labeled data via maximum correntropy criterion." IEEE transactions on cybernetics 99 (2018): 1-14.
  • Du, Bo, et al. "Multi-task learning for blind source separation." IEEE Transactions on Image Processing 27.9 (2018): 4219-4231.
  • Du, Bo, et al. "Unsupervised Scene Change Detection via Latent Dirichlet Allocation and Multivariate Alteration Detection." IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 11.12 (2018): 4676-4689.
  • Fu, Chuan, Yaohua Yi, and Fulin Luo. "Hyperspectral image compression based on simultaneous sparse representation and general-pixels." Pattern Recognition Letters 116 (2018): 65-71.
  • Li, Xue, et al. "On Gleaning Knowledge From Cross Domains by Sparse Subspace Correlation Analysis for Hyperspectral Image Classification." IEEE Transactions on Geoscience and Remote Sensing (2018).
  • Luo, Fulin, et al. "Feature learning using spatial-spectral hypergraph discriminant analysis for hyperspectral image." IEEE transactions on cybernetics 99 (2018): 1-14.
  • Luo, Fulin, et al. "Adaptive Weighted Total Variation Minimization Based Alternating Direction Method of Multipliers for Limited Angle CT Reconstruction." IEEE Access 6 (2018): 64225-64236.
  • Sun, Weiwei, et al. "A randomized subspace learning based anomaly detector for hyperspectral imagery." Remote Sensing 10.3 (2018): 417.
  • Tang, Xinyao, et al. "On combining active and transfer learning for medical data classification." IET Computer Vision 13.2 (2018): 194-205.
  • Wu, Chen, Bo Du, and Liangpei Zhang. "Hyperspectral anomalous change detection based on joint sparse representation." ISPRS Journal of Photogrammetry and Remote Sensing 146 (2018): 137-150.
  • Wu, Ke, et al. "Hyperspectral image target detection via integrated background suppression with adaptive weight selection." Neurocomputing 315 (2018): 59-67.
  • Xu, Yonghao, et al. "Hyperspectral image classification via a random patches network." ISPRS journal of photogrammetry and remote sensing 142 (2018): 344-357.
  • Xu, Yonghao, et al. "Spectral-spatial unified networks for hyperspectral image classification." IEEE Transactions on Geoscience and Remote Sensing 99 (2018): 1-17.
  • Zhang, Lefei, et al. "Simultaneous spectral-spatial feature selection and extraction for hyperspectral images." IEEE transactions on cybernetics 48.1 (2018): 16-28.
  • Zhu, Qikui, et al. "Exploiting interslice correlation for MRI prostate image segmentation, from recursive neural networks aspect." Complexity 2018 (2018).
  • Zhu, Qikui, et al. "Shape prior constrained PSO model for bladder wall MRI segmentation." Neurocomputing 294 (2018): 19-28.
  • 董燕妮, et al. "基于局域自适应信息理论测度学习的高光谱目标探测方法." 武汉大学学报信息科学版 43.8 (2018): 1271-1277.
  • Zhao Rui, et al. "GSEAD: Graphical Scoring Estimation for Hyperspectral Anomaly Detection." IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (2017): 1-15.
  • Liu Rong, et al. "Multiobjective Optimized Endmember Extraction for Hyperspectral Image." Remote Sensing 9.6 (2017): 558.
  • Chang Shizhen, et al. "IBRS: An Iterative Background Reconstruction and Suppression Framework for Hyperspectral Target Detection." IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (2017): 1-12.
  • Zhang, Yiming, et al. "Spatially Adaptive Sparse Representation for Target Detection in Hyperspectral Images." IEEE Geoscience and Remote Sensing Letters (2017): 1-5.
  • Sun, Weiwei, et al. "A Poisson nonnegative matrix factorization method with parameter subspace clustering constraint for endmember extraction in hyperspectral imagery." ISPRS Journal of Photogrammetry and Remote Sensing 128 (2017): 27-39.
  • Dong, Yanni, et al. "Dimensionality Reduction and Classification of Hyperspectral Images Using Ensemble Discriminative Local Metric Learning." IEEE Transactions on Geoscience and Remote Sensing 55.5 (2017): 2509-2524.
  • Dong, Yanni, et al. "LAM 3 L: Locally adaptive maximum margin metric learning for visual data classification." Neurocomputing 235 (2017): 1-9.
  • Sun, Weiwei, et al. "A Sparse and Low-Rank Near-Isometric Linear Embedding Method for Feature Extraction in Hyperspectral Imagery Classification." IEEE Transactions on Geoscience and Remote Sensing (2017).
  • Wu, Chen, Liangpei Zhang, and Bo Du. "Kernel slow feature analysis for scene change detection." IEEE Transactions on Geoscience and Remote Sensing 55.4 (2017): 2367-2384.
  • Du, Bo, et al. "Robust and Discriminative Labeling for Multi-Label Active Learning Based on Maximum Correntropy Criterion." IEEE Transactions on Image Processing 26.4 (2017): 1694-1707.
  • Du, Bo, et al. "Stacked convolutional denoising auto-encoders for feature representation." IEEE transactions on cybernetics 47.4 (2017): 1017-1027.
  • Wang, Zengmao, et al. "A Novel Semisupervised Active-Learning Algorithm for Hyperspectral Image Classification." IEEE Transactions on Geoscience and Remote Sensing (2017).
  • Li, Xue, et al. "Iterative Reweighting Heterogeneous Transfer Learning Framework for Supervised Remote Sensing Image Classification." IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (2017).
  • Dong, Yanni, et al. "Exploring locally adaptive dimensionality reduction for hyperspectral image classification: A maximum margin metric learning aspect." IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 10.3 (2017): 1136-1150.
  • Xiong, Wei, et al. "Combining local and global: Rich and robust feature pooling for visual recognition." Pattern Recognition 62 (2017): 225-235.
  • Xu, Mingming, et al. "A Mutation Operator Accelerated Quantum-Behaved Particle Swarm Optimization Algorithm for Hyperspectral Endmember Extraction." Remote Sensing 9.3 (2017): 197.
  • Zhao, Rui, Bo Du, and Liangpei Zhang. "Hyperspectral Anomaly Detection via a Sparsity Score Estimation Framework." IEEE Transactions on Geoscience and Remote Sensing (2017).
  • Zhang, Yuxiang, et al. "Joint Sparse Representation and Multitask Learning for Hyperspectral Target Detection." IEEE Transactions on Geoscience and Remote Sensing 55.2 (2017): 894-906.
  • Liu, Rong, Liangpei Zhang, and Bo Du. "A Novel Endmember Extraction Method for Hyperspectral Imagery Based on Quantum-Behaved Particle Swarm Optimization." IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (2017).
  • Du, Bo, et al. "PLTD: Patch-Based Low-Rank Tensor Decomposition for Hyperspectral Images." IEEE Transactions on Multimedia 19.1 (2017): 67-79.
  • Du, Bo, et al. "Exploring representativeness and informativeness for active learning." IEEE transactions on cybernetics 47.1 (2017): 14-26.
  • Zhao, Rui, et al. "A robust background regression based score estimation algorithm for hyperspectral anomaly detection." ISPRS Journal of Photogrammetry and Remote Sensing 122 (2016): 126-144.
  • Du, Bo, et al. "Beyond the sparsity-based target detector: A hybrid sparsity and statistics-based detector for hyperspectral images." IEEE Transactions on Image Processing 25.11 (2016): 5345-5357.
  • Du, Bo, et al. "Hyperspectral signal unmixing based on constrained non-negative matrix factorization approach." Neurocomputing 204 (2016): 153-161.
  • Zhang, Fan, et al. "Weakly Supervised Learning Based on Coupled Convolutional Neural Networks for Aircraft Detection." IEEE Transactions on Geoscience and Remote Sensing 54.9 (2016): 5553-5563.
  • Du, Bo, et al. "A spectral-spatial based local summation anomaly detection method for hyperspectral images." Signal Processing 124 (2016): 115-131.
  • Liu, Rong, Bo Du, and Liangpei Zhang. "Hyperspectral Unmixing via Double Abundance Characteristics Constraints Based NMF." Remote Sensing 8.6 (2016): 464.
  • Zhang, Fan, et al. "Hierarchical feature learning with dropout k-means for hyperspectral image classification." Neurocomputing 187 (2016): 75-82.
  • Zhao, Rui, et al. "Beyond Background Feature Extraction: An Anomaly Detection Algorithm Inspired by Slowly Varying Signal Analysis." IEEE Transactions on Geoscience and Remote Sensing 54.3 (2016): 1757-1774.
  • Zhang, Fan, Bo Du, and Liangpei Zhang. "Scene classification via a gradient boosting random convolutional network framework." IEEE Transactions on Geoscience and Remote Sensing 54.3 (2016): 1793-1802.
  • Zhang, Yuxiang, et al. "A low-rank and sparse matrix decomposition-based Mahalanobis distance method for hyperspectral anomaly detection." IEEE Transactions on Geoscience and Remote Sensing 54.3 (2016): 1376-1389.
  • Wang, Zengmao, et al. "A batch-mode active learning framework by querying discriminative and representative samples for hyperspectral image classification." Neurocomputing 179 (2016): 88-100.
  • Xu, Mingming, et al. "An image-based endmember bundle extraction algorithm using reconstruction error for hyperspectral imagery."Neurocomputing 173 (2016): 397-405.
  • Wang, Zengmao, et al. "A batch-mode active learning framework by querying discriminative and representative samples for hyperspectral image classification." Neurocomputing 179.C(2016):88-100.
  • Wang, Nan, et al. "An Abundance Characteristic-Based Independent Component Analysis for Hyperspectral Unmixing." IEEE Transactions on Geoscience and Remote Sensing 53.1(2015):416-428.
  • Dong, Yanni, et al. "Maximum margin metric learning based target detection for hyperspectral images." ISPRS Journal of Photogrammetry and Remote Sensing 108(2015):138-150.
  • Zhang, Yuxiang, B. Du, and L. Zhang. "A Sparse Representation-Based Binary Hypothesis Model for Target Detection in Hyperspectral Images."IEEE Transactions on Geoscience and Remote Sensing 53.3(2015):1346-1354.
  • Dong, Yanni, B. Du, and L. Zhang. "Target Detection Based on Random Forest Metric Learning." IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 8.4(2015):1830-1838.
  • Du, Bo, et al. "A hypothesis independent subpixel target detector for hyperspectral Images." Signal Processing 110(2015):244-249.
  • Zhang, Lefei, et al. "A sparse and discriminative tensor to vector projection for human gait feature representation." Signal Processing106.C(2015):245–252.
  • Zhang, Lefei, et al. "Compression of hyperspectral remote sensing images by tensor approach." Neurocomputing 147.1(2015):358–363.
  • Wu, Chen, L. Zhang, and B. Du. "Hyperspectral anomaly change detection with slow feature analysis." Neurocomputing 151(2015):175-187.
  • Shi, Qian, B. Du, and L. Zhang. "Spatial coherence-based batch-mode active learning for remote sensing image classification. " IEEE Transactions on Image Processing 24.7(2015):2037.
  • Zhang, Lefei, et al. "Ensemble manifold regularized sparse low-rank approximation for multiview feature embedding." Pattern Recognition 48.10(2015):3102-3112.
  • Zhang, Fan, B. Du, and L. Zhang. "Saliency-Guided Unsupervised Feature Learning for Scene Classification." IEEE Transactions on Geoscience and Remote Sensing 53.4(2014):2175-2184.
  • Du, Bo, and Liangpei Zhang. "A discriminative metric learning based anomaly detection method." IEEE Transactions on Geoscience and Remote Sensing 52.11 (2014): 6844-6857.
  • Zhang, Lefei, et al. "Hyperspectral remote sensing image subpixel target detection based on supervised metric learning." IEEE Transactions on Geoscience and Remote Sensing 52.8 (2014): 4955-4965.
  • Wang, Ting, Bo Du, and Liangpei Zhang. "An automatic robust iteratively reweighted unstructured detector for hyperspectral imagery." IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 7.6 (2014): 2367-2382.
  • Xu, Mingming, Bo Du, and Liangpei Zhang. "Spatial-spectral information based abundance-constrained endmember extraction methods." IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 7.6 (2014): 2004-2015.
  • Wu, Chen, Bo Du, and Liangpei Zhang. "Slow feature analysis for change detection in multispectral imagery." IEEE Transactions on Geoscience and Remote Sensing 52.5 (2014): 2858-2874.
  • Zhao, Rui, Bo Du, and Liangpei Zhang. "A robust nonlinear hyperspectral anomaly detection approach." IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 7.4 (2014): 1227-1234.
  • Du, Bo, and Liangpei Zhang. "Target detection based on a dynamic subspace." Pattern Recognition 47.1 (2014): 344-358.
  • Liu, Rong, Bo Du, and Liangpei Zhang. "Endmember number estimation for hyperspectral imagery based on vertex component analysis." Journal of Applied Remote Sensing 8.1 (2014): 085093-085093.
  • Zhang, Yuxiang, Bo Du, and Liangpei Zhang. "Regularization framework for target detection in hyperspectral imagery." IEEE Geoscience and Remote Sensing Letters 11.1 (2014): 313-317.
  • Du, Bo, et al. "Unsupervised transfer learning for target detection from hyperspectral images." Neurocomputing 120 (2013): 72-82.
  • Wang, Ting, Bo Du, and Liangpei Zhang. "A background self-learning framework for unstructured target detectors." IEEE Geoscience and Remote Sensing Letters 10.6 (2013): 1577-1581.
  • Shi, Qian, Liangpei Zhang, and Bo Du. "Semisupervised discriminative locally enhanced alignment for hyperspectral image classification." IEEE Transactions on Geoscience and Remote Sensing 51.9 (2013): 4800-4815.
  • Du, Bo, and Liangpei Zhang. "Random-selection-based anomaly detector for hyperspectral imagery." IEEE Transactions on Geoscience and Remote sensing 49.5 (2011): 1578-1589.

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