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  • 姓名：杜博
  • 主页：
  • 性别：男
  • 职称：教授
  • 学历学位：博士
  • 电话：13871461059
  • 办公地点：计算机学院大楼 A509
  • E-mail：gunspace@163.com,remoteking@whu.edu.cn
  • 硕/博士生导师：博士生导师
  • 研究兴趣
  • 教育背景
  • 工作经验
  • 教授课程
  • 发表论文
  • 研究课题
  • 研究团队
  • 获奖信息
  • 学术服务
外围投注365院长助理，“珞珈学者”特聘教授，湖北省杰青，博士生导师，IEEE Senior Member，图像处理领域SCI二区期刊Neurocomputing的Associate Editor，IEEE ACCESS的Associate Editor，图像处理领域著名会议ICPR和IJCNN的Area chair，人工智能领域CCF A类顶会AAAI和IJCAI的Senior PC Member。主要从事人工智能、计算机视觉和图像处理等方面的研究工作，近五年主持和参与相关纵向研究课题30余项，其中主持国家自然科学基金2项、军委科技委创新特区项目1项、教育部总装备部联合基金1项、973子课题1项、国家自然科学基金重点项目子课题1项、国家博士后科学基金1项、湖北省自然科学基金2项。出版著作1部，发表SCI论文共计79篇，第一、通讯作者SCI论文40篇（包含二区以上31篇、IEEE长文16篇），论文总被引用2400余次（Google Scholar, H-index=26），SCI总被引1124次，SCI他引817次，ESI高引论文10篇，ESI热点论文6篇。申请/获批国家发明专利10项，其中授权4项、转让1项。研究论文被评为IEEE智能系统与图像处理大会最佳论文、教育部博士论坛优秀学术论文、两次评为湖北省自然科学优秀学术论文。荣获国际计算机学会学术新星奖“2015 ACM Rising Star Award”，被评选为“IEEE Best Reviewer”，入选 “全国博士后特别资助计划”、湖北省“优秀博士后资助基金”、“武汉市晨光青年科技人才计划”等人才计划。

主要研究方向为人工智能、数据挖掘、模式识别、计算机视觉和图像处理。具体研究内容包括：
深度学习与图像场景理解；
迁移学习与分类研究；
稀疏学习与目标识别；
图像变化检测；
盲信号分解理论；
医学图像处理和癌变细胞诊断。
 
热忱欢迎有志向的学子加入我的研究小组，感受技术革新给视觉和图像处理领域带来的日新月异发展，一同在自主创新中完善自我、实现自我！
本课题组秉承以树人为本的宗旨，以学生的成就为荣，积极引导每位研究生成就属于他们自己的未来，为各位提供优越的科研环境和良好的科研氛围，并努力为各位创造与国际学术权威交流的机会。
 
欢迎登录我们的团队网址：http://sigma.whu.edu.cn/

快讯：
2018.3.29            外围投注365人工智能樱花论坛顺利举行
2018.2.14            课题组宋俍辰同学参加 AAAI 2018
2017.12.28          杜博教授获评武汉大学第八届“我心目中的好导师”荣誉称号
2017.11.10          课题组一篇论文入选 ESI 高被引论文
2017.10.14          小组研究生参加 CCCV 2017
2017.9.5              小组研究生参加第四届全国成像光谱技术与应用研讨会
2017.8.25            课题组王增茂博士研究生参加 IJCAI
2017.7.23            课题组博士研究生参加 IGARSS 并做分组报告
2017.7.20            课题组一篇论文被 CCF A 类期刊 IEEE TKDE 录用
2017.6.30            课题组一篇论文被 IEEE GRSL 录用
2017.5.1              课题组两篇论文被 CCF A 类会议 IJCAI 录用
2005/9 - 2010/7，武汉大学，工学博士
2001/9 - 2005/6，武汉大学，工学学士
2015/11 –至今，武汉大学，计算机学院，教授
2014/10 –2015/10，悉尼科技大学，量子计算与智能系统中心，研究员
2013/1 –2015/10，武汉大学，计算机学院，副教授
2012/7 –2012/12，武汉大学，计算机学院，讲师
2010/7 –2012/6，武汉大学，计算机学院，博士后
《物联网定位技术》、《研究生前沿课程》、《面向对象程序设计》、《多媒体技术》




近5年发表SCI二区及以上论文：
期刊名称 影响因子（中科院分区） 总篇数 第一/通信篇数
IEEE Transactions on Geoscience and Remote Sensing 3.360 （2 区TOP） 20 7
IEEE Transactions on Image Processing 3.735（2 区） 3 3
IEEE Transactions on Cybernetics 4.943（1 区TOP） 3 4
IEEE Transactions on Multimedia 3.509（2 区） 1 1
IEEE Transactions on Knowledge and Data Engineering 3.438（2 区） 1 1
ISPRS Journal of Photogrammetry and Remote Sensing 4.188（1 区） 2 2
Remote Sensing 3.036（2 区） 1 1
Pattern Recognition 3.399（2 区） 3 3
Information Sciences 3.364（2 区） 1 1
Neurocomputing 2.392（2 区） 8 6
Signal Processing 2.063（2 区） 3 3
合计 45 31
 
近年小组论文详列：
[1]     B. Du，X. Tang, L. Zhang etc. "Robust Graph-based Semi-supervised Learning for Noisy Labeled Data via Maximum Correntropy Criterion," IEEE Transactions on Cybernetics, DOI (identifier) 10.1109/TCYB.2018.2804326, 2018.
[2]     B. Du, Z. Huang, N. Wang, L. Zhang, “A Band-wise Noise Model combined with Low-rank Matrix Factorization for Hyperspectral Image Denoising,” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, DOI (identifier) 10.1109/JSTARS.2018.2805290, 2018.
[3]     B. Du，Z. Wang, etc. “Robust and Discriminative Labeling for Multi-label Active Learning Based on Maximum Correntropy Criterion,” IEEE Transactions on Image Processing, vol. 26, no. 4, 1694-1707, 2017.
[4]     B. Du，Y. Zhang, etc. "Beyond the Sparsity-Based Target Detector: A Hybrid Sparsity and Statistics Based Detector for Hyperspectral Images," IEEE Transactions on Image Processing, vol. 25, no. 11, pp. 5345-5357, 2016.
[5]     B. Du，M. Zhang, etc. “PLTD: Patch-Based Low-Rank Tensor Decomposition for Hyperspectral Images,” IEEE Transactions on Multimedia, vol. 19, no. 1, pp. 67-79, Jan 2017.
[6]     B. Du, X. Xiong, L. Zhang, etc., “Stacked Convolutional Denoising Auto-Encoders for Feature Representation,” IEEE Transactions on Cybernetics, vol. 47, no. 4, pp.1017-1027 Apr, 2017.
[7]     B. Du, Z. Wang, L. Zhang, etc., “Exploring Representativeness and Informativeness for Active Learning,” IEEE Transactions on Cybernetics, vol.47, no. 1, pp. 14-26, 2017.
[8]     B. Du and L. Zhang*, "A discriminative metric learning based anomaly detection method," IEEE Transactions on Geoscience and Remote Sensing, vol. 52, no. 11, pp. 6844-6857, Nov 2014.
[9]     B. Du* and L. Zhang, "Target detection based on a dynamic subspace," Pattern Recognition, vol. 47, no. 1, pp. 344-358, Jan 2014.
[10] B. Du, L. Zhang*, “Random-Selection-Based Anomaly Detector for Hyperspectral Imagery,” IEEE Transactions on Geoscience and Remote Sensing, vol. 49, no. 5, pp. 1578–1589, May, 2011.
[11] B. Du, Z. Huang, N. Wang, Y. Zhang, X. Jia, “Joint weighted nuclear norm and total variation regularization for hyperspectral image denoising,” International Journal of Remote Sensing, vol. 39, no. 2, pp. 334-355, 2018.
[12] B. Du, Y. Sun, 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, 2018.
[13] B. Du, S. Wang, N. Wang*, et al., “Hyperspectral signal unmixing based on constrained non-negative matrix factorization approach,”Neurocomputing, vol. 204, pp. 153–161, September 2016.
[14] B. Du, R. Zhao, L. Zhang, et al., “A spectral-spatial based local summation anomaly detection method for hyperspectral images,”Signal Processing, vol. 124, pp. 115–131 July 2016.
[15] B. Du, Y. Zhang, and L. Zhang*, “A hypothesis independent subpixel target detector for hyperspectral Images,” Signal Processing, vol. 110, pp. 244-249, May, 2015.
[16] B. Du*, L. Zhang, D. Tao, and D. Zhang, "Unsupervised transfer learning for target detection from hyperspectral images,"Neurocomputing, vol. 120, pp. 72-82, Nov 2013.
[17] B. Du*, L. Zhang, L. Zhang, T. Chen, K. Wu, “A Discriminative Manifold Learning Based Dimension Reduction Method for Hyperspectral Classification,” International Journal of Fuzzy Systems, vol. 14, no. 2, pp, 272-277, Jun. 2012.
[18] Q. Shi, B. Du*, and L. Zhang, “Spatial Coherence Based Batch-Mode Active Learning for Remote Sensing Images Classification,” IEEE Transactions on Image Processing, vol. 24, no. 7, pp. 2037-2050, July, 2015.
[19] Z. Wang, B. Du*, L. Zhang, L. Zhang, and X. Jia, “A Novel Semi-Supervised Active Learning Algorithm for Hyperspectral Image Classification,” IEEE Transactions on Geoscience and Remote Sensing, vol. 55, no.6, pp. 3071-3083, 2017.
[20] W. Xiong, B. Du*, etc., “Combining Local and Global: Rich and Robust Feature Pooling for Visual Recognition,” Pattern Recognition, vol. 62, pp. 225-235, February 2017.
[21] L. Zhang, X. Zhu, L. Zhang, and B. Du*, "Multidomain Subspace Classification for Hyperspectral Images," IEEE Transactions on Geoscience and Remote Sensing, vol. 54, no. 10, pp. 6138-6150, Oct. 2016.
[22] Y. Zhang, B. Du*, T. Liu, and L. Zhang, “Joint Sparse Representation and Multi-Task Learning for Hyperspectral Target Detection,”IEEE Transactions on Geoscience and Remote Sensing, vol. 55, no. 2, pp. 894 - 906, 2017.
[23] R. Zhao, B. Du*, L. Zhang, “A Robust Background Regression Based Score Estimation Algorithm for Hyperspectral Anomaly Detection,” ISPRS Journal of Photogrammetry and Remote Sensing, vol. 122, pp. 126-144, 2016.
[24] L. Zhang, Q. Zhang, B. Du*, ect., “Simultaneous Spectral-Spatial Feature Selection and Extraction for Hyperspectral Images,” IEEE Transactions on Cybernetics, DOI: 10.1109/TCYB.2016.2605044, 2016.
[25] N. Zhao, L. Zhang, B. Du*, Q. Zhang, J. You and D. Tao, “Robust Dual Clustering with Adaptive Manifold Regularization,” IEEE Transactions on Knowledge and Data Engineering, vol. 29, no. 11, pp. 2498-2509, 2017.
[26] H Wang, W Hu, Z Qiu, and B Du*, “Nodes' evolution diversity and link prediction in social networks,” IEEE Transactions on Knowledge and Data Engineering, vol. 29, no. 10, pp. 2263-2274, 2017.
[27] R. Liu, B. Du*, and L. Zhang, “Hyperspectral Unmixing via Double Abundance Characteristics Constraints Based NMF,” Remote Sensing, vol. 8, no. 6, DOI: 10.3390/rs8060464, 2016.
[28] L Zhang, Q Zhang, L Zhang, D Tao, X Huang, and B Du*, “Ensemble Manifold Regularized Sparse Low-Rank Approximation for Multiview Feature Embedding,” Pattern Recognition, vol. 48, no. 10, pp. 3102-3112, Oct. 2015.
[29] Y. Zhang, W. Ke, B. Du*, X Hu, “Independent Encoding Joint Sparse Representation and Multitask Learning for Hyperspectral Target Detection,” IEEE Geoscience and Remote Sensing Letters, vol. 14, no. 11, pp. 1933-1937, 2017.
[30] Z. Wang, B. Du*, L. Zhang, and L. Zhang, “A batch-mode active learning framework by querying discriminative and representative samples for hyperspectral image classification”, Neurocomputing, vol. 179, pp. 88-100,  February 2016.
[31] L. Zhang, L. Zhang, D. Tao, X. Huang, B. Du*, “Compression of hyperspectral remote sensing images by tensor approach,”Neurocomputing, vol. 147, pp. 358-363, Jan 2015.
[32] C. Wu, L. Zhang, and B. Du*, "Hyperspectral anomaly change detection with slow feature analysis," Neurocomputing, vol. 151, Part 1, pp. 175-187, Mar. 2015.
[33] L. Zhang, L. Zhang, D. Tao, B. Du*, “A sparse and discriminative tensor to vector projection for human gait feature representation,”Signal Processing, vol. 106, pp. 245–252, Jan 2015.
[34] Y. Dong, L. Zhang, L. Zhang, B. Du*, “Maximum margin metric learning based target detection for hyperspectral images,” ISPRS Journal of Photogrammetry and Remote Sensing, vol. 108, pp. 138–150, Oct 2015.
[35] R. Liu, B. Du*, L. Zhang, "Endmember number estimation for hyperspectral imagery based on vertex component analysis," Journal of Applied Remote Sensing，vol. 8, no. 1, 085093, vol. 8, no. 1, pp. 085093-085093, Sep 2014.
[36] W. Hu*, L. Yan, H. Wang, B. Du*, and D. Tao, “Real-time traffic jams prediction inspired by Biham, Middleton and Levine (BML) model,” Information Sciences, vol. 381, pp. 209-228, 2017.
[37] W Li, L Zhang, L Zhang, B Du*, “GPU parallel implementation of isometric mapping for hyperspectral classification,” IEEE Geoscience and Remote Sensing Letters, vol. 14, no. 9, pp. 1532-1536, 2017.
[38] Y. Dong, B. Du*, L. Zhang, L. Zhang, and D. Tao, “LAM3L: Locally Adaptive Maximum Margin Metric Learning for Visual Data Classification,” Neurocomputing, vol. 235, no. 26, pp. 1-9, 2017.
[39] Y. Zhang, K. Wu, B. Du*, L. Zhang, and X Hu, “Hyperspectral Target Detection via Adaptive Joint Sparse Representation and Multi-Task Learning with Locality Information,” Remote Sensing, vol. 9, no. 5, pp. 482-492, 2017.
[40] M. Xu, L. Zhang, B. Du*, L. Zhang, Y. Fan, and D Song, “A mutation operator accelerated quantum-behaved particle swarm optimization algorithm for hyperspectral endmember extraction,” Remote Sensing, vol. 9, no. 3, pp. 197-208, 2017.
[41] W. Hu, H. Wang, Z. Qiu, C. Nie, L. Yan, and B Du*, “An event detection method for social networks based on hybrid link prediction and quantum swarm intelligent,” World Wide Web, vol. 20, no. 4, pp. 775-795, 2017.
[42] C. Wu, L. Zhang* and B. Du, “Kernel Slow Feature Analysis for Scene Change Detection,” IEEE Transactions on Geoscience and Remote Sensing, vol. 55, no. 4, pp. 2367-2384, 2017.
[43] R. Liu, L. Zhang* and B. 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, 2016, DOI:10.1109/JSTARS.2016.2640274.
[44] R. Zhao, B. Du, L. Zhang*, “Hyperspectral Anomaly Detection via A Sparsity Score Estimation Framework”, IEEE Transactions on Geoscience and Remote Sensing, vol. 55, no. 6, pp. 3208-3222, 2017.
[45] Y. Dong, B. Du, L. Zhang, and L. Zhang*, “Dimensionality Reduction and Classification of Hyperspectral Images Using Ensemble Discriminative Local Metric Learning,” IEEE Transactions on Geoscience and Remote Sensing, vol. 55, no. 2, pp. 2509-2524, 2017.
[46] S. Chang, B. Du, L. Zhang*, and R. Zhao, "IBRS: An Iterative Background Reconstruction and Suppression Framework for Hyperspectral Target Detection," IEEE J. Sel. Topics Appl. Earth Observ. Remote Sens., DOI (identifier) 10.1109/JSTARS.2017.2676120.
[47] X. Li, L. Zhang, B. Du, L. Zhang*, and Q. Shi, "An Iterative Reweighting Heterogeneous Transfer Learning Framework for Supervised Remote Sensing Image Classification," IEEE J. Sel. Topics Appl. Earth Observ. Remote Sens., DOI: 10.1109/JSTARS.2016.2646138, 2017.
[48] L. Zhang*, B. Du, and Y. Zhong, "Hybrid Detectors Based on Selective Endmembers," IEEE Transactions on Geoscience and Remote Sensing, vol. 48, no. 6, pp. 2633-2646, June, 2010.
[49] Y. Dong, 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, vol. 8, no. 4, pp. 1830-1838, April, 2015.
[50] N. Wang, B. Du, L. Zhang*, “An Abundance Characteristic Based Independent Component Analysis for Hyperspectral Unmxing,” IEEE Trans. on Geoscience and Remote Sensing, vol. 53, no. 1, pp. 416-428, Jan. 2015.
[51] Y. Zhang, 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, vol. 53, no. 3, pp. 1346-1354, March, 2015.
[52] H. Sun, J. Li*, J. Chang, B. Du, et al., “Efficient Compressed Sensing Tracking via Mixed Classifiers' Decision,” SCIENCE CHINA Information Sciences, DOI: 10.1007/s11432-015-5424-5, 2015.
[53] C. Wu, B. Du, and L. Zhang*, "Slow Feature Analysis for Change Detection in Multispectral Imagery," IEEE Transactions on Geoscience and Remote Sensing, vol. 52, no. 5, pp. 2858-2874, May 2014.
[54] Q. Shi, L. Zhang*, and B. Du, "Semisupervised Discriminative Locally Enhanced Alignment for Hyperspectral Image Classification," IEEE Transactions on Geoscience and Remote Sensing, vol. 51, no. 9, pp. 4800-4815, Sep. 2013.
[55] L. Zhang*, C. Wu, and B. Du, "Automatic radiometric normalization for multitemporal remote sensing imagery with iterative slow feature analysis," IEEE Transactions on Geoscience and Remote Sensing, vol. 52, no. 10, pp. 6141-6155, Oct 2014.
[56] L. Zhang, L. Zhang*, D. Tao, X. Huang, and B. Du, "Hyperspectral Remote Sensing Image Subpixel Target Detection Based on Supervised Metric Learning," IEEE Transactions on Geoscience and Remote Sensing, vol. 52, no. 8, pp. 4955-4965, Aug 2014.
[57] T. Wang, B. Du, and L. Zhang*, "A Background Self-Learning Framework for Unstructured Target Detectors," IEEE Geoscience and Remote Sensing Letters, vol. 10, no. 6, pp. 1577-1581, Nov. 2013.
[58] T. Wang, B. Du, and L. Zhang*, "A Kernel-Based Target-Constrained Interference-Minimized Filter for Hyperspectral Sub-Pixel Target Detection," IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 6, no. 2, pp. 626-637, Apr. 2013.
[59] N. Wang, B. Du, and L. Zhang*, "An Endmember Dissimilarity Constrained Non-Negative Matrix Factorization Method for Hyperspectral Unmixing," IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 6, no. 2, pp. 554-569, Apr. 2013.
[60] C. Wu, B. Du, and L. Zhang*, "A Subspace-Based Change Detection Method for Hyperspectral Images," IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 6, no. 2, pp. 815-830, Feb. 2013.
[61] Y. Zhang, B. Du, and L. Zhang*, “Regularization Framework for Target Detection in Hyperspectral Imagery," IEEE Geoscience and Remote Sensing Letters, vol.11, no.1, pp. 313-317, Jan 2014.
[62] R. Zhao, B. Du, and L. Zhang*, "A Robust Nonlinear Hyperspectral Anomaly Detection Approach," IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 7, no. 4, pp. 1227-1234, Apr 2014.
[63] M. Xu, B. Du, and L. Zhang*, “Spatial-Spectral Information Based Abundance-Constrained Endmember Extraction Methods,” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 7, no. 6, pp. 2004-2015, June 2014.
[64] T. Wang, B. Du, L. Zhang*, “An Automatic Robust Iteratively Reweighted Unstructured Detector for Hyperspectral Imagery,” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 7, no. 6, pp. 2367-2382, June 2014.
[65] Y. Zhang, B. Du, and L. Zhang*, “A Nonlinear Sparse Representation Based Binary Hypothesis Model for Hyperspectral Target Detection,” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 10.1109/JSTARS.2014.2368173, 2014.
[66] M. Xu, L. Zhang*, and B. Du, “An Image-Based Endmember Bundle Extraction Algorithm Using Both Spatial and Spectral Information,” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 10.1109/JSTARS.2014.2373491, 2015.
[67] K. Wu*, L. Zhang, R. Niu, B. Du, “Super-resolution land-cover mapping based on the selective endmember spectral mixture model in hyperspectral imagery,” Optical Engineering, vol.50, no.12, pp.126201-1-14. Nov 2011.
[68] T. Chen*, R. Niu, P. Li, L. Zhang, B. Du, “Regional soil erosion risk mapping using RUSLE, GIS, and remote sensing: a case study in Miyun Watershed, North China,” Environmental Earth Sciences, vol. 63, no. 3, pp. 533-541, June, 2011.
[69] T. Chen*, R. Niu, Y. Wang, P. Li, L. Zhang, B. Du, “Assessment of spatial distribution of soil loss over the upper basin of Miyun reservoir in China based on RS and GIS techniques,” Environmental Monitoring and Assessment, vol. 179, no. 1-4, pp. 605-617, Aug 2011.
[70] R. Niu, B. Du, Y. Wang, L. Zhang, and T. Chen*, “Impact of fractional vegetation cover change on soil erosion in Miyun reservoir basin, China,” Environmental Earth Sciences, vol. 72, no.8, pp. 2741-2749, Oct 2014.
[71] M. Xu, L. Zhang, B. Du, and L. Zhang*, “An Image-Based Endmember Bundle Extraction Algorithm Using Reconstruction Error for Hyperspectral Imagery,” Neurocomputing, accept.
[72] W. Hu*, H. Liang, C. Peng, B. Du, and Q. Hu, "A hybrid chaos-particle swarm optimization algorithm for the vehicle routing problem with time window," Entropy, vol. 15, no. 14, pp. 1247-1270, April,2013.
[73] W. Hu*, C. Fan, J. Luo, C. Peng, and B. Du, "An on‐demand data broadcasting scheduling algorithm based on dynamic index strategy,"Wireless Communications and Mobile Computing, vol. 13, no. 10,July,2013.
[74] W. Hu*, H. Wang, B. Du, and L. Yan, "A multi-intersection model and signal timing plan algorithm for urban traffic signal control,"Transport, pp. 1-11, Aug,2014.
[75] W. Hu*, B. Du, Y. Wu, H. Liang, C. Peng, and Q. Hu, "A hybrid column generation algorithm based on metaheuristic optimization,"Transport, pp. 1-19, Oct,2013.
[76] W. Hu*, H. Wang, C. Peng, H. Wang, H. Liang, and B. Du, "An outer–inner fuzzy cellular automata algorithm for dynamic uncertainty multi-project scheduling problem," Soft Computing, pp. 1-22, August ,2014
[77] W. Sun*, L. Zhang, B. Du, W. Li, and Y. Mark Lai, “Band Selection Using Improved Sparse Subspace Clustering for Hyperspectral Imagery Classification,” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 8, no. 6, pp. 2784-2797, 2015.
[78] Y. Tao, M. Xu*, F. Zhang, B. Du, L. Zhang, “Unsupervised-Restricted Deconvolutional Neural Network for Very High Resolution Remote-Sensing Image Classification,” IEEE Transactions on Geoscience and Remote Sensing, vol. 55, no. 12, pp. 6805-6823, 2017.
[79] Y. Zhang, B. Du, Y. Zhang, and L. Zhang*, “Spatially Adaptive Sparse Representation for Target Detection in Hyperspectral Images,”IEEE Geoscience and Remote Sensing Letters, vol. 14, no. 11, pp. 1923-1927, 2017.
 
Conference Papers 
[1]   R. Zhao, X. Han, B. Du, L. Zhang, “Sparsity Score Estimation for Hyperspectral Anomaly Detection,” Proceedings of the 4th IEEE/IIAE International Conference on Intelligent Systems and Image Processing 2016(ICISIP). (Best Paper Award)
[2]   Z. Wang, B. Du, etc., “On Gleaning Knowledge from Multiple Domains for Active Learning”, 26th International Joint Conference on Artificial Intelligence (IJCAI 2017).
[3]   L. Zhang, Q. Zhang, B. Du, etc., “Adaptive Manifold Regularized Matrix Factorization for Data Clustering” 26th International Joint Conference on Artificial Intelligence (IJCAi 2017).
[4]   L. Zhang, Q. Zhang, B. Du*, ect., “Robust manifold matrix factorization for joint clustering and feature extraction,” the Thirty-First AAAI Conference on Artificial Intelligence (AAAI-17).
[5]   Z Wang, B Du*, L Zhang, L Zhang, M Fang, D Tao, “Multi-label Active Learning Based on Maximum Correntropy Criterion: Towards Robust and Discriminative Labeling,” 2016 European Conference on Computer Vision(ECCV), pp. 453-468.
[6]   W. Xiong, B. Du*, L Zhang, et al., “SCDAE: Stacked Convolutional Denoising Autoencoders towards Robust Unsuperived Feature Representation,” 2016 The Annual International Joint Conference on Neural Networks(IJCNN).
[7]   N. Zhao, L. Zhang and B. Du*, “Sparse Tensor Discriminative Locality Alignment for Gait Recognition,” 2016 The Annual International Joint Conference on Neural Networks(IJCNN).
[8]   W. Xiong, B. Du*, L Zhang, et al., “Regularizing Deep Convolutional Neural Networks with a Structured Decorrelation  Constraint”2016 IEEE International Conference on Data Mining (ICDM).
[9]   W. Xiong, B. Du*, L Zhang, et al., “R2FP: rich and robust feature pooling for mining visual data,” 2015 IEEE International Conference on Data Mining (ICDM), pp. 469-478.
[10] Q. Zhang, L. Zhang*, B. Du, et al., “MMFE: Multitask Multiview Feature Embedding,” 2015 IEEE International Conference on Data Mining (ICDM), pp. 1105-1110.
[11] B. Du, M. Zhang, L. Zhang*, X. Li, "Hyperspectral biological images compression based on multiway tensor projection," in 2014 IEEE International Conference on Multimedia and Expo, (ICME).
[12] B. Du, N. Wang*, and D. Tao, “A Spectral Dissimilarity Constrained Nonnegative Matrix factorization based Cancer Screening Algorithm from Hyperspectral Fluorescence Images” in 2012 International Conference on Computerized Healthcare (ICCH 2012), 2012.
[13] B. Du*, N. Wang, and D. Tao, “Hyperspectral medical images unmixing for cancer screening based on rotational independent component analysis,” in International Conference on Intelligence Science and Big Data Engineering (IScIDE 2013), 2013.
[14] B. Du, L. Zhang*, and L. Zhang, “A Manifold Learning based Feature Extraction Method for Hyperspectral Classification,” in Second International Conference on Information Science and Technology, vol. ISSU, pp. 491-494, 2012.
[15] B. Du*, D. Zhang, P.  Li, T.  Chen, and K. Wu, “A structured sub-pixel target detection method base on manifold learning method,”Proc. SPIE 8002, MIPPR 2011: Multispectral Image Acquisition, Processing, and Analysis, pp. 80020N, December 2011.
[16] B. Du*, K. Wu, L. Zhang, and T. Chen, “An Unstructured Sub-pixel Target Detector for Hyperspectral Imagery,” in 2010 International Conference on Computer Application and System Modeling vol. 11 ISSU, pp.V11469-V11472, 2010.
[17] B. Du*, and L. Zhang, “Robust Metric based Anomaly Detection in Kernel Feature Space,” in XXII Congress of the International Society for Photogrammetry and Remote Sensing (ISPRS 2012), vol. XXXIX-B7, 2012.
[18] Q. Shi, B. Du* and L. Zhang , “An novel active learning strategy for hyperspectral image classification,” in 4th IEEE GRSS Workshop on Hyperspectral Image and Signal Processing: evolution in remote sensing (WHISPERS 2012).
[19] C. Wu, L. Zhang and B. Du*, “Targeted Change Detection For Stacked Multi-Temporal Hyperspectral Image,” in 4th IEEE GRSS Workshop on Hyperspectral Image and Signal Processing: evolution in remote sensing (WHISPERS 2012).
[20] N. Wang, L. Zhang and B. Du*, “An Endmember Dissimilarity Based Non-negative Matrix Factorization Method for Hyperspectral Unmixing,” in 4th IEEE GRSS Workshop on Hyperspectral Image and Signal Processing: evolution in remote sensing (WHISPERS 2012).
[21] M. Xu, L. Zhang and B. Du*, “An endmember extraction framework based on abundance constraint,” in 4th IEEE GRSS Workshop on Hyperspectral Image and Signal Processing: evolution in remote sensing (WHISPERS 2012).
专利情况：
一种高光谱遥感影像异常探测方法（专利号：201010130302，专利已经成功转让。）
一种慢特征分析的高光谱影像变化检测方法（专利号：201310689353.2）
一种高光谱图像混合像元分解算法（专利号：201610206981.4）
一种基于量子粒子群算法的高光谱图像端元提取算法（专利号：201610205990.1）
一种基于量子优化的高光谱遥感影像端元提取方法（专利号：201610157103.8）
一种基于非局部和低秩分解的高光谱图像压缩方法（专利号：201610157079.8）
一种高光谱遥感影像目标探测方法（专利号：201610156117.8）
一种高光谱遥感影像端元提取方法（专利号：201610156222.1）
基于稳健背景回归的高光谱遥感影像异常目标探测方法（专利号：201610156116.3）
一种基于图构造的高光谱遥感影像异常目标探测方法（专利号：201610156118.2）

[1] 国家自然科学基金面上项目，61471274， “稀疏表达和跨领域学习的高光谱遥感图像亚像元目标探测研究”，2015-2018，82万，主持。

[2] 国家自然科学基金重点项目，41431175，“数据驱动的高光谱遥感影像特征表达、迁移学习及其在城市地理信息提取中的应用”，2015-2018，130万，排名第二。

[3] 国家自然科学基金青年基金项目，61102128，“端元可变的高光谱图像亚像元目标探测研究”，2011-2014，26万，主持。

[4] 国家“973”项目子课题 ，2012CB719905，“高分辨率数据精处理和空间信息智能转化的理论与方法”， 2012-2016，135万，主持。

[5] 军委科技委创新特区项目，17-H863-01-ZT-005-011-01，“面向"吉林一号"视频卫星大数据的超分辨率重建和目标跟踪技术”，2017-2018，100万，主持。

[6] 总装备部-教育部联合基金，6141A02022329，“高光谱遥感图像混合目标探测与识别”，2018-2019，主持。

[7] 湖北省自然科学基金，2014CFB193，“基于荧光图像模式识别的早期癌变区域探测研究”， 2015-2016，6万，主持。

[8] 中央高校基本科研业务费学科交叉项目，2042014kf0239，“模式识别理论与癌变细胞诊断”，2014-2015，30万，主持。

[9] 珞珈青年学者（特聘教授）专项基金，“模式识别理论与计算机视觉研究”，2013-2015，20万，主持。

[10] 中国博士后科学基金，2011T0123，“基于多特征和优化融合的高光谱影像异常目标探测研究”，2010-2012，3万，主持。

[11] 中国博士后特别资助，2012T50670，“基于多探测器优化融合高光谱影像林火探测研究”，2012-2014，15万，主持。

[12] 长江水利委员会长江科学院开放研究基金，CKWV2016380/KY，“空天地一体化实时的高拱坝形变综合安全监控理论与方法”，2016-2018，5万，主持。

[13] 浙江大学CAD&CG国家重点实验室开放课题，“基于流形结构信息的大数据主动学习方法研究”，2016-2017，2万，主持。

[14] 中国科学院数字地球重点实验室开放基金，2010LED006，“基于流形学习模型的图像亚像元目标探测研究”，2010-2011，6万，主持。

[15] 湖北省自然科学基金，2011CDB455，“基于多探测器优化融合的高光谱图像异常目标探测研究”，2011-2012，4万，主持。

[16] 湖北省博士后科技活动基金，180947，“基于优化融合的林区火情检测方法研究”，2012-2013，8万，主持。

[17] 中央高校基本科研业务费专项资金，111104，“亚像元目标探测研究”，2010-2011，5万，主持。

[18] 国防科大外协高分专项，250000148，“图像目标探测与分类技术”，2013-2014，20万，主持。

[19] 国家海洋局海洋专项，250000106，“极端大风、降水下海洋生态环境响应的综合影响评估方法研究及准业务化决策支持系统”， 2012-2014，19万，主持。

[20] 国家自然科学基金重点项目，40930532，“多源高分辨率卫星影像的几何精处理、特征提取与智能化分类”，2010-2014，5万，参与。

[21] 国家自然科学基金面上项目，41271376，“遥感影像大范围地表信息缺失区域的修复理论与方法研究”，2013-2016，2万，参与。

[22] 国家高技术研究发展计划（863），“高光谱遥感影像的光谱分解、目标探测与定位技术研究”，2009-2010，副组长。

[23] 总参XX项目，“光学图像地物要素智能化提取技术”，2011-2013，5万，参与。

[24] 国家“973”项目子课题，2011CB707100，“空天地一体化对地观测传感网的理论与方法—面向任务的对地观测传感网信息聚焦服务模型”，2010-2012，10万，参与。


教师：
张乐飞  副教授
张玉香  副研究员
孙伟伟 博士后
武辰  博士后


研究生：

张帆 (2+3硕博连读) 2014级博士生
赵锐 (2+3硕博连读) 2014级博士生
董燕妮 (2+3硕博连读) 2014级博士生
刘蓉 (1+4博士连续) 2015级博士生
王增茂 2016级博士生 
熊维 2014级保送生（珠峰计划“弘毅班”）
章梦飞 2014级保送生
王少东 2014级硕士生
朱晓杰 2014级硕士生
孙雨佳 2014级硕士生
李雪  2015级硕士生（1+4博士连续）
黄志强 2015级硕士生
唐新瑶 2015级保送生
朱其奎 2015级硕士生 (2+3硕博连读) 
李万 2015级硕士生
钟永建2016级保送生（物理学基地班）
宋俍辰2016级保送生（数学基地班）
徐永浩2016级保送生（1+4博士连续）
张祎铭2016级保送生
常世桢2016级保送生（1+4博士连续）
王勇2016级保送生
肖攀2016级保送生

本科生：
蔡诗晗 保送生
夏海峰 保送生
曾梓龙
普佳萌（出国读博）
毛凤玲（保送上海科大）

毕业生去向：
王挺 2014届博士毕业生：香港中文大学 助理研究员，博士后
王楠 2014届博士毕业生：中国科学院遥感与数字地球研究所 助理研究员
石茜 2015届博士毕业生：中山大学 旅游与规划学院，博士后，讲师
许明明2016届博士毕业生：中国石油大学 地球科学与技术学院，博士后，讲师
熊绍龙2016届硕士研究生：广州中科沃土金融公司
林昱坤2016届硕士毕业生：中科院遥感与数字地球研究所 攻读博士

2016年 IEEE International Conference on Intelligent Systems and Image Processing 2016(ICISIP) Best Paper Award

2015年 国际计算机学会学术新星奖

2015年 IEEE Senior Member

2015年 湖北省自然科学优秀论文奖

2014年 The 18th Asia Pacific Symposium on Intelligent and Evolutionary Systems国际大会的分会场主席

2013年 武汉大学“珞珈青年学者”

2013年 湖北省自然科学优秀论文奖

2012年 担任 IEEE Workshop on Hyperspectral Image and Signal Processing: Evolution and Remote Sensing 的 Session Chair (“IEEE 分会场主席”)

2011年 IEEE BEST REVIEWER (“IEEE 最佳审稿人”)

2010年 武汉大学优秀博士科研成果展

2009年 全国测绘学科博士论坛优秀论文奖



·            The Association for the Advance of Artificial Intelligence 2017\2018国际会议，高级程序委员会委员
·             International Conference on Pattern Recognition 2018, 区域主席
·            The IEEE International Geoscience and Remote Sensing Symposium 2016国际会议，分会主席
·            The 11th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Application (VISIGRAPP 2016)国际会议，程序委员会委员
·            2015 International Conference on Fuzzy System and Data Mining（FSDM2015）国际会议，组委会成员
·            The 19th Asia Pacific Symposium on Intelligent and Evolutionary Systems (IES 2015)国际会议，组委会成员
·            The 18th Asia Pacific Symposium on Intelligent and Evolutionary Systems (IES 2014)国际会议，分会主席
·             IEEE Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS 2014)国际会议，组委会成员
·             IEEE Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS 2012)国际会议，分会主席
·             图像处理领域权威期刊“IEEE Trans. Image Process”、 “IEEE Trans. Signal Process” 、“IEEE Trans. Geosci. Remote Sens.”等近20个国际学术刊物和《计算机学报》、《软件学报》、《中国图象图形学报》、《光子学报》等10个国内核心学术期刊审稿人