Ping Zhong
Ping Zhong
Verified email at nudt.edu.cn
Title
Cited by
Cited by
Year
A multiple conditional random fields ensemble model for urban area detection in remote sensing optical images
P Zhong, R Wang
IEEE Transactions on Geoscience and Remote Sensing 45 (12), 3978-3988, 2007
1622007
Learning to diversify deep belief networks for hyperspectral image classification
P Zhong, Z Gong, S Li, CB Schönlieb
IEEE Transactions on Geoscience and Remote Sensing 55 (6), 3516-3530, 2017
1522017
Learning conditional random fields for classification of hyperspectral images
P Zhong, R Wang
IEEE transactions on image processing 19 (7), 1890-1907, 2010
1272010
Explaining explanations: An approach to evaluating interpretability of machine learning
LH Gilpin, D Bau, BZ Yuan, A Bajwa, M Specter, L Kagal
arXiv preprint arXiv:1806.00069, 2018
122*2018
Multiple-spectral-band CRFs for denoising junk bands of hyperspectral imagery
P Zhong, R Wang
IEEE Transactions on Geoscience and Remote Sensing 51 (4), 2260-2275, 2012
832012
Modeling and classifying hyperspectral imagery by CRFs with sparse higher order potentials
P Zhong, R Wang
IEEE Transactions on Geoscience and Remote Sensing 49 (2), 688-705, 2010
662010
Dynamic learning of SMLR for feature selection and classification of hyperspectral data
P Zhong, P Zhang, R Wang
IEEE Geoscience and Remote Sensing Letters 5 (2), 280-284, 2008
652008
Active learning with Gaussian process classifier for hyperspectral image classification
S Sun, P Zhong, H Xiao, R Wang
IEEE Transactions on Geoscience and Remote Sensing 53 (4), 1746-1760, 2014
542014
A CNN with multiscale convolution and diversified metric for hyperspectral image classification
Z Gong, P Zhong, Y Yu, W Hu, S Li
IEEE Transactions on Geoscience and Remote Sensing 57 (6), 3599-3618, 2019
442019
Diversity-promoting deep structural metric learning for remote sensing scene classification
Z Gong, P Zhong, Y Yu, W Hu
IEEE Transactions on Geoscience and Remote Sensing 56 (1), 371-390, 2017
442017
Learning sparse CRFs for feature selection and classification of hyperspectral imagery
P Zhong, R Wang
IEEE transactions on geoscience and remote sensing 46 (12), 4186-4197, 2008
442008
Jointly learning the hybrid CRF and MLR model for simultaneous denoising and classification of hyperspectral imagery
P Zhong, R Wang
IEEE Transactions on Neural Networks and Learning Systems 25 (7), 1319-1334, 2014
412014
Using combination of statistical models and multilevel structural information for detecting urban areas from a single gray-level image
P Zhong, R Wang
IEEE transactions on geoscience and remote sensing 45 (5), 1469-1482, 2007
372007
Unsupervised representation learning with deep convolutional neural network for remote sensing images
Y Yu, Z Gong, P Zhong, J Shan
International Conference on Image and Graphics, 97-108, 2017
292017
An unsupervised convolutional feature fusion network for deep representation of remote sensing images
Y Yu, Z Gong, C Wang, P Zhong
IEEE Geoscience and Remote Sensing Letters 15 (1), 23-27, 2017
262017
A MRF Model-Based Active Learning Framework for the Spectral-Spatial Classification of Hyperspectral Imagery
S Sun, Z Ping, H Xiao, R Wang
IEEE Journal of Selected Topics in Signal Processing 9 (6), 1074 - 1088, 2015
262015
Object detection based on combination of conditional random field and markov random field
P Zhong, R Wang
18th International Conference on Pattern Recognition (ICPR'06) 3, 160-163, 2006
182006
-Regularized Deconvolution Network for the Representation and Restoration of Optical Remote Sensing Images
J Zhang, P Zhong, Y Chen, S Li
IEEE transactions on geoscience and remote sensing 52 (5), 2617-2627, 2013
172013
Image segmentation based on Markov random fields with adaptive neighborhood systems
P Zhong, R Wang
Optical Engineering 45 (9), 097202, 2006
132006
Multiscale dynamic graph convolutional network for hyperspectral image classification
S Wan, C Gong, P Zhong, B Du, L Zhang, J Yang
IEEE Transactions on Geoscience and Remote Sensing 58 (5), 3162-3177, 2019
122019
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