Hyperspectral Image Classification Based on Parameter-Optimized 3D-CNNs Combined with Transfer Learning and Virtual Samples
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Salah Bourennane | Xuefeng Liu | Yue Meng | Min Fu | Qiaoqiao Sun | S. Bourennane | Min Fu | Xuefeng Liu | Qiaoqiao Sun | Y. Meng
[1] Nitish Srivastava,et al. Improving neural networks by preventing co-adaptation of feature detectors , 2012, ArXiv.
[2] Guizhong Liu,et al. An efficient macroblock-based diverse and flexible prediction modes selection for hyperspectral images coding , 2010, Signal Process. Image Commun..
[3] Meng Wang,et al. Active learning in multimedia annotation and retrieval: A survey , 2011, TIST.
[4] Gwanggil Jeon,et al. Hyperspectral image compression based on lapped transform and Tucker decomposition , 2015, Signal Process. Image Commun..
[5] D. B. Megherbi,et al. A robust multi-stage information-theoretic approach for registration of partially overlapped hyperspectral aerial imagery and evaluation in the presence of system noise , 2017, Signal Process. Image Commun..
[6] Shuying Li,et al. Structure Preserving Transfer Learning for Unsupervised Hyperspectral Image Classification , 2017, IEEE Geoscience and Remote Sensing Letters.
[7] M. Bauer,et al. Airborne hyperspectral remote sensing to assess spatial distribution of water quality characteristics in large rivers: the Mississippi River and its tributaries in Minnesota. , 2013 .
[8] Jon Atli Benediktsson,et al. A spatial-spectral kernel-based approach for the classification of remote-sensing images , 2012, Pattern Recognit..
[9] Weifeng Liu,et al. Multiview Canonical Correlation Analysis Networks for Remote Sensing Image Recognition , 2017, IEEE Geoscience and Remote Sensing Letters.
[10] Qingquan Li,et al. Three-dimensional local binary patterns for hyperspectral imagery classification , 2017, 2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS).
[11] Qian Du,et al. Hyperspectral Classification Based on Texture Feature Enhancement and Deep Belief Networks , 2018, Remote. Sens..
[12] Ying Li,et al. Spectral-Spatial Classification of Hyperspectral Imagery with 3D Convolutional Neural Network , 2017, Remote. Sens..
[13] Xiao Xiang Zhu,et al. Deep Recurrent Neural Networks for Hyperspectral Image Classification , 2017, IEEE Transactions on Geoscience and Remote Sensing.
[14] Gangyao Kuang,et al. SAR Target Recognition via Local Sparse Representation of Multi-Manifold Regularized Low-Rank Approximation , 2018, Remote. Sens..
[15] Juha Suomalainen,et al. Generation of Spectral–Temporal Response Surfaces by Combining Multispectral Satellite and Hyperspectral UAV Imagery for Precision Agriculture Applications , 2015, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.
[16] Qingshan Liu,et al. Spatiotemporal Satellite Image Fusion Using Deep Convolutional Neural Networks , 2018, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.
[17] Ivan Laptev,et al. Learning and Transferring Mid-level Image Representations Using Convolutional Neural Networks , 2014, 2014 IEEE Conference on Computer Vision and Pattern Recognition.
[18] Xiangtao Zheng,et al. Spectral–Spatial Kernel Regularized for Hyperspectral Image Denoising , 2015, IEEE Transactions on Geoscience and Remote Sensing.
[19] 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.
[20] 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.
[21] Meng Wang,et al. Unified Video Annotation via Multigraph Learning , 2009, IEEE Transactions on Circuits and Systems for Video Technology.
[22] Jun Li,et al. 3D-Gabor Inspired Multiview Active Learning for Spectral-Spatial Hyperspectral Image Classification , 2018, Remote. Sens..
[23] Weifeng Liu,et al. Multiview dimension reduction via Hessian multiset canonical correlations , 2018, Inf. Fusion.
[24] Bin Wang,et al. Graph-based deep Convolutional networks for Hyperspectral image classification , 2016, 2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS).
[25] Bo Du,et al. Slow Feature Analysis for Change Detection in Multispectral Imagery , 2014, IEEE Transactions on Geoscience and Remote Sensing.
[26] Yoshua Bengio,et al. Practical Recommendations for Gradient-Based Training of Deep Architectures , 2012, Neural Networks: Tricks of the Trade.
[27] Soumith Chintala,et al. Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks , 2015, ICLR.
[28] Caroline Fossati,et al. Reduction of Signal-Dependent Noise From Hyperspectral Images for Target Detection , 2014, IEEE Transactions on Geoscience and Remote Sensing.
[29] Dapeng Tao,et al. Manifold regularized kernel logistic regression for web image annotation , 2013, Neurocomputing.
[30] Qian Du,et al. Hyperspectral Image Spatial Super-Resolution via 3D Full Convolutional Neural Network , 2017, Remote. Sens..
[31] 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.
[32] Stefan Winkler,et al. Ground-based image analysis: A tutorial on machine-learning techniques and applications , 2016, IEEE Geoscience and Remote Sensing Magazine.
[33] J. Chanussot,et al. Hyperspectral Remote Sensing Data Analysis and Future Challenges , 2013, IEEE Geoscience and Remote Sensing Magazine.
[34] Barnali M. Dixon,et al. Application of Support Vector Machines for Landuse Classification Using High-Resolution RapidEye Images: A Sensitivity Analysis , 2015 .
[35] Zongxu Pan,et al. Transfer Learning with Deep Convolutional Neural Network for SAR Target Classification with Limited Labeled Data , 2017, Remote. Sens..
[36] Antonio J. Plaza,et al. Robust Matrix Discriminative Analysis for Feature Extraction From Hyperspectral Images , 2017, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.
[37] Wen Liu,et al. Learning Change from Synthetic Aperture Radar Images: Performance Evaluation of a Support Vector Machine to Detect Earthquake and Tsunami-Induced Changes , 2016, Remote. Sens..
[38] Alessandro Chiuso,et al. The harmonic analysis of kernel functions , 2017, Autom..
[39] 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.
[40] Naoto Yokoya,et al. Potential of Resolution-Enhanced Hyperspectral Data for Mineral Mapping Using Simulated EnMAP and Sentinel-2 Images , 2016, Remote. Sens..
[41] A-Li Luo,et al. Restricted Boltzmann machine: a non-linear substitute for PCA in spectral processing , 2015 .
[42] Lorenzo Bruzzone,et al. Domain Adaptation for the Classification of Remote Sensing Data: An Overview of Recent Advances , 2016, IEEE Geoscience and Remote Sensing Magazine.
[43] Caroline Fossati,et al. Denoising of Hyperspectral Images Using the PARAFAC Model and Statistical Performance Analysis , 2012, IEEE Transactions on Geoscience and Remote Sensing.
[44] Qiang Yang,et al. A Survey on Transfer Learning , 2010, IEEE Transactions on Knowledge and Data Engineering.
[45] Pabitra Mitra,et al. BASS Net: Band-Adaptive Spectral-Spatial Feature Learning Neural Network for Hyperspectral Image Classification , 2016, IEEE Transactions on Geoscience and Remote Sensing.
[46] Francesca Bovolo,et al. Updating Land-Cover Maps by Classification of Image Time Series: A Novel Change-Detection-Driven Transfer Learning Approach , 2013, IEEE Transactions on Geoscience and Remote Sensing.
[47] Gang Wang,et al. Deep Learning-Based Classification of Hyperspectral Data , 2014, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.
[48] D. Anguita,et al. K-fold generalization capability assessment for support vector classifiers , 2005, Proceedings. 2005 IEEE International Joint Conference on Neural Networks, 2005..
[49] Sasa Nikolic,et al. Multi-channel descriptors and ensemble of Extreme Learning Machines for classification of remote sensing images , 2015, Signal Process. Image Commun..
[50] Gang Wang,et al. Learning Contextual Dependencies with Convolutional Hierarchical Recurrent Neural Networks , 2015, ArXiv.
[51] Yoshua Bengio,et al. Deep Sparse Rectifier Neural Networks , 2011, AISTATS.
[52] Ke Lu,et al. $p$-Laplacian Regularized Sparse Coding for Human Activity Recognition , 2016, IEEE Transactions on Industrial Electronics.
[53] Xiao Xiang Zhu,et al. A Self-Improving Convolution Neural Network for the Classification of Hyperspectral Data , 2016, IEEE Geoscience and Remote Sensing Letters.
[54] R. Valentini,et al. Biodiversity Mapping in a Tropical West African Forest with Airborne Hyperspectral Data , 2014, PloS one.
[55] Qingshan Liu,et al. Matrix-Based Discriminant Subspace Ensemble for Hyperspectral Image Spatial–Spectral Feature Fusion , 2016, IEEE Transactions on Geoscience and Remote Sensing.
[56] J R Fielding,et al. Spiral CT in the evaluation of flank pain: overall accuracy and feature analysis. , 1997, Journal of computer assisted tomography.
[57] Matthew D. Zeiler. ADADELTA: An Adaptive Learning Rate Method , 2012, ArXiv.
[58] F. M. Lacar,et al. Use of hyperspectral imagery for mapping grape varieties in the Barossa Valley, South Australia , 2001, IGARSS 2001. Scanning the Present and Resolving the Future. Proceedings. IEEE 2001 International Geoscience and Remote Sensing Symposium (Cat. No.01CH37217).
[59] Geunseop Lee,et al. Fast computation of the compressive hyperspectral imaging by using alternating least squares methods , 2018, Signal Process. Image Commun..
[60] Bo Du,et al. Spectral–Spatial Unified Networks for Hyperspectral Image Classification , 2018, IEEE Transactions on Geoscience and Remote Sensing.
[61] Gui-Song Xia,et al. Learning High-level Features for Satellite Image Classification With Limited Labeled Samples , 2015, IEEE Transactions on Geoscience and Remote Sensing.
[62] Weizhou Zhao,et al. Secure Fingerprint Recognition Based on Frobenius Norm , 2012, 2012 International Conference on Computer Science and Electronics Engineering.
[63] Yi Shen,et al. 3D gray-gradient-gradient tensor field feature for hyperspectral image classification , 2015, 2015 10th International Conference on Communications and Networking in China (ChinaCom).