Content-Guided Convolutional Neural Network for Hyperspectral Image Classification
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Liang Xiao | Jonathan Cheung-Wai Chan | Jingxiang Yang | Qichao Liu | J. Chan | Jingxiang Yang | Qichao Liu | Liang Xiao
[1] Haokui Zhang,et al. Spectral-spatial classification of hyperspectral imagery using a dual-channel convolutional neural network , 2017 .
[2] Jonathan Cheung-Wai Chan,et al. Learning and Transferring Deep Joint Spectral–Spatial Features for Hyperspectral Classification , 2017, IEEE Transactions on Geoscience and Remote Sensing.
[3] Bor-Chen Kuo,et al. A Kernel-Based Feature Selection Method for SVM With RBF Kernel for Hyperspectral Image Classification , 2014, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.
[4] Zhiming Luo,et al. Spectral–Spatial Residual Network for Hyperspectral Image Classification: A 3-D Deep Learning Framework , 2018, IEEE Transactions on Geoscience and Remote Sensing.
[5] Xiuping Jia,et al. Deep Feature Extraction and Classification of Hyperspectral Images Based on Convolutional Neural Networks , 2016, IEEE Transactions on Geoscience and Remote Sensing.
[6] Gang Wang,et al. Deep Learning-Based Classification of Hyperspectral Data , 2014, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.
[7] Fan Zhang,et al. Deep Convolutional Neural Networks for Hyperspectral Image Classification , 2015, J. Sensors.
[8] Jonathan Cheung-Wai Chan,et al. Hyperspectral image classification using two-channel deep convolutional neural network , 2016, 2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS).
[9] Chunhui Zhao,et al. Spatial Logistic Regression for Support-Vector Classification of Hyperspectral Imagery , 2017, IEEE Geoscience and Remote Sensing Letters.
[10] Chen Chen,et al. Classification of Hyperspectral Data Using a Multi-Channel Convolutional Neural Network , 2018, ICIC.
[11] Jun Zhou,et al. Hyperspectral Image Classification Based on Structured Sparse Logistic Regression and Three-Dimensional Wavelet Texture Features , 2013, IEEE Transactions on Geoscience and Remote Sensing.
[12] Yi Li,et al. Deformable Convolutional Networks , 2017, 2017 IEEE International Conference on Computer Vision (ICCV).
[13] Yanfeng Gu,et al. Discriminative Multiple Kernel Learning for Hyperspectral Image Classification , 2016, IEEE Transactions on Geoscience and Remote Sensing.
[14] Paul M. Mather,et al. An assessment of the effectiveness of decision tree methods for land cover classification , 2003 .
[15] Andrew Zisserman,et al. Spatial Transformer Networks , 2015, NIPS.
[16] Jimmy Ba,et al. Adam: A Method for Stochastic Optimization , 2014, ICLR.
[17] Xiao Xiang Zhu,et al. Deep Recurrent Neural Networks for Hyperspectral Image Classification , 2017, IEEE Transactions on Geoscience and Remote Sensing.
[18] Peijun Du,et al. (Semi-) Supervised Probabilistic Principal Component Analysis for Hyperspectral Remote Sensing Image Classification , 2014, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.
[19] Liang Xiao,et al. Multi-layer boosting sparse convolutional model for generalized nuclear segmentation from histopathology images , 2019, Knowl. Based Syst..
[20] Geoffrey E. Hinton,et al. ImageNet classification with deep convolutional neural networks , 2012, Commun. ACM.
[21] Deyu Meng,et al. Integration of 3-dimensional discrete wavelet transform and Markov random field for hyperspectral image classification , 2017, Neurocomputing.
[22] Jun Li,et al. Advanced Spectral Classifiers for Hyperspectral Images: A review , 2017, IEEE Geoscience and Remote Sensing Magazine.
[23] Alberto Signoroni,et al. Deep Learning Meets Hyperspectral Image Analysis: A Multidisciplinary Review , 2019, J. Imaging.
[24] Antonio J. Plaza,et al. New Postprocessing Methods for Remote Sensing Image Classification: A Systematic Study , 2014, IEEE Transactions on Geoscience and Remote Sensing.
[25] François Chollet,et al. Xception: Deep Learning with Depthwise Separable Convolutions , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[26] Geoffrey E. Hinton,et al. Learning representations by back-propagating errors , 1986, Nature.
[27] Jon Atli Benediktsson,et al. Multiple Morphological Profiles From Multicomponent-Base Images for Hyperspectral Image Classification , 2014, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.
[28] Pedram Ghamisi,et al. Spectral–Spatial Classification of Hyperspectral Images Based on Hidden Markov Random Fields , 2014, IEEE Transactions on Geoscience and Remote Sensing.
[29] Sergey Ioffe,et al. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift , 2015, ICML.
[30] Yuan Yu,et al. TensorFlow: A system for large-scale machine learning , 2016, OSDI.
[31] Wenju Wang,et al. A Fast Dense Spectral-Spatial Convolution Network Framework for Hyperspectral Images Classification , 2018, Remote. Sens..
[32] Dumitru Erhan,et al. Going deeper with convolutions , 2014, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[33] Lorenzo Bruzzone,et al. Classification of hyperspectral remote sensing images with support vector machines , 2004, IEEE Transactions on Geoscience and Remote Sensing.
[34] Timothy A. Warner,et al. Kernel-based extreme learning machine for remote-sensing image classification , 2013 .
[35] Liang Xiao,et al. Hyperspectral image clustering via sparse dictionary-based anchored regression , 2019, IET Image Process..
[36] Yuan Yan Tang,et al. Spectral–Spatial Shared Linear Regression for Hyperspectral Image Classification , 2017, IEEE Transactions on Cybernetics.
[37] Qian Du,et al. Hyperspectral Image Classification Using Deep Pixel-Pair Features , 2017, IEEE Transactions on Geoscience and Remote Sensing.
[38] Jian Sun,et al. Deep Residual Learning for Image Recognition , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[39] Johannes R. Sveinsson,et al. Spectral and spatial classification of hyperspectral data using SVMs and morphological profiles , 2008, 2007 IEEE International Geoscience and Remote Sensing Symposium.
[40] Kilian Q. Weinberger,et al. Densely Connected Convolutional Networks , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[41] Xing Zhao,et al. Spectral–Spatial Classification of Hyperspectral Data Based on Deep Belief Network , 2015, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.
[42] Nikolaos Doulamis,et al. Deep supervised learning for hyperspectral data classification through convolutional neural networks , 2015, 2015 IEEE International Geoscience and Remote Sensing Symposium (IGARSS).
[43] Lorenzo Bruzzone,et al. Classification of Hyperspectral Images With Regularized Linear Discriminant Analysis , 2009, IEEE Transactions on Geoscience and Remote Sensing.
[44] Qingshan Liu,et al. Cascaded Recurrent Neural Networks for Hyperspectral Image Classification , 2017, IEEE Transactions on Geoscience and Remote Sensing.
[45] Ying Li,et al. Spectral-Spatial Classification of Hyperspectral Imagery with 3D Convolutional Neural Network , 2017, Remote. Sens..
[46] Jiayi Ma,et al. Hyperspectral Image Classification With Robust Sparse Representation , 2016, IEEE Geoscience and Remote Sensing Letters.
[47] Liang Xiao,et al. Contour-Seed Pairs Learning-Based Framework for Simultaneously Detecting and Segmenting Various Overlapping Cells/Nuclei in Microscopy Images , 2018, IEEE Transactions on Image Processing.
[48] Bidyut Baran Chaudhuri,et al. HybridSN: Exploring 3-D–2-D CNN Feature Hierarchy for Hyperspectral Image Classification , 2019, IEEE Geoscience and Remote Sensing Letters.
[49] Melba M. Crawford,et al. Manifold-Learning-Based Feature Extraction for Classification of Hyperspectral Data: A Review of Advances in Manifold Learning , 2014, IEEE Signal Processing Magazine.
[50] Deyu Meng,et al. Hyperspectral Image Classification With Markov Random Fields and a Convolutional Neural Network , 2017, IEEE Transactions on Image Processing.