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Ming Hao
Ming Hao
School of Environment Science and Spatial Informatics, China University of Mining and Technology
Dirección de correo verificada de cumt.edu.cn
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Año
Change detection method for remote sensing images based on an improved Markov random field
W Gu, Z Lv, M Hao
Multimedia Tools and Applications 76, 17719-17734, 2017
1762017
Robust optical-to-SAR image matching based on shape properties
Y Ye, L Shen, M Hao, J Wang, Z Xu
IEEE Geoscience and Remote Sensing Letters 14 (4), 564-568, 2017
1262017
Unsupervised change detection with Expectation-Maximization-based level set
M Hao, W Shi, H Zhang, C Li
IEEE Geoscience and Remote Sensing Letters 11 (1), 2014
942014
Novel Approach to Unsupervised Change Detection Based on a Robust Semi-Supervised FCM Clustering Algorithm
P Shao, W Shi, P He, M Hao, X Zhang
Remote Sensing, 2016
802016
A Novel Adaptive Fuzzy Local Information -Means Clustering Algorithm for Remotely Sensed Imagery Classification
H Zhang, Q Wang, W Shi, M Hao
IEEE Transactions on Geoscience and Remote Sensing 55 (9), 5057-5068, 2017
792017
FSDAF 2.0: Improving the performance of retrieving land cover changes and preserving spatial details
D Guo, W Shi, M Hao, X Zhu
Remote Sensing of Environment 248, 111973, 2020
742020
Change detection based on Gabor wavelet features for very high resolution remote sensing images
Z Li, W Shi, H Zhang, M Hao
IEEE Geoscience and Remote Sensing Letters 14 (5), 783-787, 2017
702017
Unsupervised change detection using fuzzy c-means and MRF from remotely sensed images
M Hao, H Zhang, W Shi, K Deng
Remote Sensing Letters 4 (12), 2013
662013
Large-scale deformation monitoring in mining area by D-InSAR and 3D laser scanning technology integration
B Chen, K Deng, H Fan, M Hao
International Journal of Mining Science and Technology 23 (4), 555-561, 2013
572013
Accuracy assessment measures for object extraction from remote sensing images
L Cai, W Shi, Z Miao, M Hao
Remote Sensing 10 (2), 303, 2018
562018
A novel dynamic threshold method for unsupervised change detection from remotely sensed images
P He, W Shi, H Zhang, M Hao
Remote Sensing Letters 5 (4), 2014
322014
An advanced superpixel-based Markov random field model for unsupervised change detection
M Hao, M Zhou, J Jin, W Shi
IEEE Geoscience and Remote Sensing Letters 17 (8), 1401-1405, 2019
262019
An object-based change detection approach using uncertainty analysis for VHR images
M Hao, W Shi, K Deng, H Zhang, P He
Journal of Sensors, 2016
232016
Analysis of spatial distribution pattern of change-detection error caused by misregistration
W Shi, M Hao
International Journal of Remote Sensing 34 (19), 2013
232013
Level set evolution with local uncertainty constraints for unsupervised change detection
X Zhang, W Shi, P Liang, M Hao
Remote Sensing Letters 8 (8), 811-820, 2017
222017
A method to detect earthquake-collapsed buildings from high-resolution satellite images
W Shi, M Hao
Remote Sensing Letters 4 (12), 2013
222013
Enhanced spatially constrained remotely sensed imagery classification using a fuzzy local double neighborhood information c-means clustering algorithm
H Zhang, L Bruzzone, W Shi, M Hao, Y Wang
IEEE Journal of Selected Topics in Applied Earth Observations and Remote …, 2018
182018
Unsupervised change detection using a novel fuzzy c-means clustering simultaneously incorporating local and global information
M Hao, Z Hua, Z Li, B Chen
Multimedia Tools and Applications 76, 20081-20098, 2017
182017
Classification of very high spatial resolution imagery based on pixel shape features set and spectral information
H Zhang, Y Wang, W Shi, M Hao, Z Miao
IEEE Geoscience and Remote Sensing Letters 11 (5), 2014
18*2014
Unsupervised change detection using spectral features and a texture difference measure for VHR remote-sensing images
Z Li, W Shi, M Hao, H Zhang
International journal of remote sensing 38 (23), 7302-7315, 2017
172017
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