欢迎到访李伟主页


   

李伟

教授、博士生导师

北京化工大学

信息科学与技术学院

English Webpage

邮件: liw@mail.buct.edu.cn

办公室: 科技大厦517

地址: 北京市北三环东路15号北京化工大学4号信箱

 

 


个人基本信息:


部分科研项目:


代表性论文:

[36] 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.

[35] 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, DOI: 10.3390/sr9040323, March 2017.

[34] W. Li, G. Wu, F. Zhang, and Q. Du, “Hyperspectral Image Classification Using Deep Pixel-Pair Features,” IEEE Transactions on Geoscience and Remote Sensing, vol. 55, no. 2, pp. 844-853, February 2017. [Matlab code]

[33] 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.

[32] W. Li and Q. Du, “A Survey on Representation-Based Classification and Detection in Hyperspectral Remote Sensing Imagery,” Pattern Recognition Letters, vol. 83, pp. 115-123, November 2016. [Matlab code]

[31] 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.

[30] W. Li, L. Wu, X. Qiu, Q. Ran, and X. Xie, “Parallel Computation for Blood Cell Classification in Medical Hyperspectral Imagery,” Measurement Science and Technology, vol. 27, no. 9, article ID. 095102, July 2016.

[29] W. Li, J. Liu, and Q. Du, “Sparse and Low Rank Graph-Based Discriminant Analysis for Hyperspectral Image Classification,” IEEE Transactions on Geoscience and Remote Sensing, vol. 54, no. 7, pp. 4094-4105, July 2016. [Matlab code]

[28] 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. [ESI Highly Cited Paper]

[27] L. Huang, C. Chen, W. Li*, and Q. Du, “Remote Sensing Image Scene Classification Using Multi-Scale Completed Local Binary Patterns and Fisher Vectors,” Remote Sensing, vol. 8, no. 6, June 2016.

[26] 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, December 2015. [Matlab code]

[25] 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, December 2015.

[24] B. Peng, W. Li*, X. Xie*, Q. Du, and K. Liu, “Weighted Fusion-Based Representation Classifiers for Hyperspectral Imagery,” Remote Sensing, vol. 7, no. 11, pp. 14806-14826, November 2015.

[23] 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. [Matlab code] [ESI Highly Cited Paper]

[22] 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.

[21] 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, March 2015. [Matlab code] [ESI Highly Cited Paper]

[20] W. Li and Q. Du, “Decision Fusion for Dual-Window Based Hyperspectral Anomaly Detector,” Journal of Applied Remote Sensing, vol. 9, no. 1, article ID. 097297, February 2015.

[19] 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, February 2015. [Matlab code]

[18] 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, January 2015. [Matlab code] [ESI Highly Cited Paper]

[17] J. Zou, W. Li*, X. Huang, and Q. Du, “Classification of Hyperspectral Urban Data Using Adaptive Simultaneous Orthogonal Matching Pursuit,” Journal of Applied Remote Sensing, vol. 8, no. 1, article ID. 085099, July 2014.

[16] M. Xiong, F. Zhang, Q. Ran, W. Hu, and W. Li*, “Representation-based Classifications with Markov Random Field Model for Hyperspectral Urban Data,” Journal of Applied Remote Sensing, vol. 8, no. 1, article ID. 085097, July 2014. [Matlab code]

[15] 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. [Matlab code]

[14] W. Li, S. Prasad, and J. E. Fowler, “Decision Fusion in Kernel-Induced Spaces for Hyperspectral Image Classification,” IEEE Transactions on Geoscience and Remote Sensing, vol. 52, no. 6, pp. 3399-3411, June 2014. [Matlab code]

[13] C. Chen, W. Li*, H. Su, and K. Liu, “Spectral-Spatial Classification of Hyperspectral Image Based on Kernel Extreme Learning Machine,” Remote Sensing, vol. 6, no. 6, pp. 5795-5814, June 2014.

[12] C. Chen, W. Li*, E. W. Tramel, M. Cui, S. Prasad, and J. E. Fowler, “Spectral-Spatial Preprocessing Using Multihypothesis Prediction for Noise-Robust Hyperspectral Image Classification,” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 7, no. 4, pp. 1047-1059, April 2014.

[11] 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. [Matlab code]

[10] W. Li, K. Liu, and H. Su, “Wavelet-Based Nearest Regularized Subspace for Noise-Robust Hyperspectral Image Classification,” Journal of Applied Remote Sensing, vol. 8, no. 1, article ID. 083665, March 2014.

[9] W. Li, E. W. Tramel, S. Prasad, and J. E. Fowler, “Nearest Regularized Subspace for Hyperspectral Classification,” IEEE Transactions on Geoscience and Remote Sensing, vol. 52, no. 1, pp. 477-489, January 2014.[Matlab code] [ESI Highly Cited Paper]

[8] C. Chen, W. Li, E. W. Tramel, and J. E. Fowler, “Reconstruction of Hyperspectral Imagery from Random Projections Using Multihypothesis Prediction,” IEEE Transactions on Geoscience and Remote Sensing, vol. 52, no. 1, pp. 365-374, January 2014.

[7] W. Li, S. Prasad, and J. E. Fowler, “Hyperspectral Image Classification Using Gaussian Mixture Model and Markov Random Field,” IEEE Geoscience and Remote Sensing Letters, vol. 11, no. 1, pp. 153-157, January 2014. [Matlab code]

[6] W. Li, S. Prasad, and J. E. Fowler, “Integration of Spectral-Spatial Information for Hyperspectral Image Reconstruction from Compressive Random Projections,” IEEE Geoscience and Remote Sensing Letters, vol. 10, no. 6, pp. 1379-1383, November 2013.

[5] W. Li, S. Prasad, and J. E. Fowler, “Noise-Adjusted Subspace Discriminant Analysis for Hyperspectral Imagery Classification,” IEEE Geoscience and Remote Sensing Letters, vol. 10, no. 6, pp. 1374-1378, November 2013.

[4] W. Li, S. Prasad, and J. E. Fowler, “Classification and Reconstruction from Random Projections for Hyperspectral Imagery,” IEEE Transactions on Geoscience and Remote Sensing, vol. 51, no. 2, pp. 833-843, February 2013. [Matlab code]

[3] S. Prasad, W. Li, J. E. Fowler, and L. Bruce, “Information Fusion in the Redundant-Wavelet-Transform Domain for Noise-Robust Hyperspectral Classification,” IEEE Transactions on Geoscience and Remote Sensing, vol. 50, no. 9, pp. 3474-3486, September 2012.

[2] W. Li, S. Prasad, J. E. Fowler, and L. Bruce, “Locality Preserving Dimensionality Reduction and Classification for Hyperspectral Image Analysis,” IEEE Transactions on Geoscience and Remote Sensing, vol. 50, no. 4, pp. 1185-1198, April 2012. [Matlab code] [ESI Highly Cited Paper]

[1] W. Li, S. Prasad, J. E. Fowler, and L. Bruce, “Locality Preserving Discriminant Analysis in Kernel Induced Feature Spaces for Hyperspectral Image Classification,” IEEE Geoscience and Remote Sensing Letters, vol. 8, no. 5, pp. 894-898, September 2011.



HTML Hit Counter