Semisupervised classification for hyperspectral image based on multi-decision labeling and deep feature learning
暂无分享,去创建一个
Xiaorui Ma | Hongyu Wang | Jie Wang | Hongyu Wang | Jie Wang | Xiaorui Ma
[1] Antonio J. Plaza,et al. A Novel Semi-Supervised Method for Obtaining Finer Resolution Urban Extents Exploiting Coarser Resolution Maps , 2014, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.
[2] Lorenzo Bruzzone,et al. Active and Semisupervised Learning for the Classification of Remote Sensing Images , 2014, IEEE Transactions on Geoscience and Remote Sensing.
[3] Bin Wang,et al. A Novel Spatial–Spectral Similarity Measure for Dimensionality Reduction and Classification of Hyperspectral Imagery , 2014, IEEE Transactions on Geoscience and Remote Sensing.
[4] Amin Alizadeh Naeini,et al. Improving the Dynamic Clustering of Hyperspectral Data Based on the Integration of Swarm Optimization and Decision Analysis , 2014, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.
[5] Bo Du,et al. Deep Learning for Remote Sensing Data: A Technical Tutorial on the State of the Art , 2016, IEEE Geoscience and Remote Sensing Magazine.
[6] Jon Atli Benediktsson,et al. Semisupervised Self-Learning for Hyperspectral Image Classification , 2013, IEEE Transactions on Geoscience and Remote Sensing.
[7] Melba M. Crawford,et al. View Generation for Multiview Maximum Disagreement Based Active Learning for Hyperspectral Image Classification , 2012, IEEE Transactions on Geoscience and Remote Sensing.
[8] Bo Du,et al. Ensemble manifold regularized sparse low-rank approximation for multiview feature embedding , 2015, Pattern Recognit..
[9] Liangpei Zhang,et al. An unsupervised artificial immune classifier for multi/hyperspectral remote sensing imagery , 2006, IEEE Trans. Geosci. Remote. Sens..
[10] Raviv Raich,et al. A generative semi-supervised model for multi-view learning when some views are label-free , 2013, 2013 IEEE International Conference on Acoustics, Speech and Signal Processing.
[11] Xin Huang,et al. A multi-index learning approach for classification of high-resolution remotely sensed images over urban areas , 2014 .
[12] Richard G. Baraniuk,et al. Sparsity and Structure in Hyperspectral Imaging : Sensing, Reconstruction, and Target Detection , 2014, IEEE Signal Processing Magazine.
[13] Trac D. Tran,et al. Hyperspectral Image Classification via Kernel Sparse Representation , 2013, IEEE Trans. Geosci. Remote. Sens..
[14] Gustavo Camps-Valls,et al. Semi-Supervised Graph-Based Hyperspectral Image Classification , 2007, IEEE Transactions on Geoscience and Remote Sensing.
[15] Jun Li,et al. A novel semi-supervised hyperspectral image classification approach based on spatial neighborhood information and classifier combination , 2015 .
[16] Tsehaie Woldai,et al. Multi- and hyperspectral geologic remote sensing: A review , 2012, Int. J. Appl. Earth Obs. Geoinformation.
[17] Zhenfeng Shao,et al. A Novel Hierarchical Semisupervised SVM for Classification of Hyperspectral Images , 2014, IEEE Geoscience and Remote Sensing Letters.
[18] Shihong Du,et al. Learning multiscale and deep representations for classifying remotely sensed imagery , 2016 .
[19] Jon Atli Benediktsson,et al. Advances in Hyperspectral Image Classification: Earth Monitoring with Statistical Learning Methods , 2013, IEEE Signal Processing Magazine.
[20] Jie Geng,et al. Hyperspectral image classification via contextual deep learning , 2015, EURASIP Journal on Image and Video Processing.
[21] Xiaojin Zhu,et al. --1 CONTENTS , 2006 .
[22] Robert B. Fisher,et al. Special issue on animal and insect behaviour understanding in image sequences , 2015, EURASIP J. Image Video Process..
[23] Liangpei Zhang,et al. An Adaptive Memetic Fuzzy Clustering Algorithm With Spatial Information for Remote Sensing Imagery , 2014, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.
[24] Antonio J. Plaza,et al. A Subspace-Based Multinomial Logistic Regression for Hyperspectral Image Classification , 2014, IEEE Geoscience and Remote Sensing Letters.
[25] Daniel Jiwoong Im,et al. Semisupervised Hyperspectral Image Classification via Neighborhood Graph Learning , 2015, IEEE Geoscience and Remote Sensing Letters.
[26] G. F. Hughes,et al. On the mean accuracy of statistical pattern recognizers , 1968, IEEE Trans. Inf. Theory.
[27] Yuan Yan Tang,et al. Manifold-Based Sparse Representation for Hyperspectral Image Classification , 2014, IEEE Transactions on Geoscience and Remote Sensing.
[28] Nicolas Courty,et al. Multiclass feature learning for hyperspectral image classification: sparse and hierarchical solutions , 2015, ArXiv.
[29] Antonio J. Plaza,et al. Subspace-Based Support Vector Machines for Hyperspectral Image Classification , 2015, IEEE Geoscience and Remote Sensing Letters.
[30] Thomas Burger,et al. PerTurbo Manifold Learning Algorithm for Weakly Labeled Hyperspectral Image Classification , 2014, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.
[31] Ying Wang,et al. Semi-supervised classification for hyperspectral imagery based on spatial-spectral Label Propagation , 2014 .
[32] Jon Atli Benediktsson,et al. A Survey on Spectral–Spatial Classification Techniques Based on Attribute Profiles , 2015, IEEE Transactions on Geoscience and Remote Sensing.
[33] Ujjwal Maulik,et al. Learning with transductive SVM for semisupervised pixel classification of remote sensing imagery , 2013 .
[34] Yuan Yan Tang,et al. Hyperspectral Image Classification Based on Regularized Sparse Representation , 2014, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.
[35] Liangpei Zhang,et al. On Combining Multiple Features for Hyperspectral Remote Sensing Image Classification , 2012, IEEE Transactions on Geoscience and Remote Sensing.
[36] Qiang Song,et al. Modified Co-Training With Spectral and Spatial Views for Semisupervised Hyperspectral Image Classification , 2014, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.
[37] Saeid Homayouni,et al. An Improved FCM Algorithm Based on the SVDD for Unsupervised Hyperspectral Data Classification , 2013, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.
[38] J. Chanussot,et al. Hyperspectral Remote Sensing Data Analysis and Future Challenges , 2013, IEEE Geoscience and Remote Sensing Magazine.
[39] Qian Du,et al. Semisupervised Discriminant Analysis for Hyperspectral Imagery With Block-Sparse Graph , 2015, IEEE Geoscience and Remote Sensing Letters.
[40] Rui Zhang,et al. Semi-Supervised Hyperspectral Image Classification Using Spatio-Spectral Laplacian Support Vector Machine , 2014, IEEE Geoscience and Remote Sensing Letters.
[41] Antonio J. Plaza,et al. Spectral–Spatial Classification of Hyperspectral Data Using Local and Global Probabilities for Mixed Pixel Characterization , 2014, IEEE Transactions on Geoscience and Remote Sensing.