Local Manifold Learning-Based L Ma, MM Crawford, J Tian
IEEE Transactions on Geoscience and Remote Sensing 48 (11), 4099-4109, 2010
581 2010 Stacked denoise autoencoder based feature extraction and classification for hyperspectral images C Xing, L Ma, X Yang
Journal of Sensors 2016 (1), 3632943, 2016
266 2016 Local-manifold-learning-based graph construction for semisupervised hyperspectral image classification L Ma, MM Crawford, X Yang, Y Guo
IEEE Transactions on Geoscience and Remote Sensing 53 (5), 2832-2844, 2014
127 2014 Anomaly detection for hyperspectral images based on robust locally linear embedding L Ma, MM Crawford, J Tian
Journal of Infrared, Millimeter, and Terahertz Waves 31, 753-762, 2010
100 2010 Discriminative transfer joint matching for domain adaptation in hyperspectral image classification J Peng, W Sun, L Ma, Q Du
IEEE Geoscience and Remote Sensing Letters 16 (6), 972-976, 2019
93 2019 Exploring nonlinear manifold learning for classification of hyperspectral data MM Crawford, L Ma, W Kim
Optical Remote Sensing: Advances in signal processing and exploitation …, 2011
81 2011 Centroid and covariance alignment-based domain adaptation for unsupervised classification of remote sensing images L Ma, MM Crawford, L Zhu, Y Liu
IEEE Transactions on Geoscience and Remote Sensing 57 (4), 2305-2323, 2018
75 2018 Graph-based semi-supervised learning for spectral-spatial hyperspectral image classification L Ma, A Ma, C Ju, X Li
pattern recognition letters 83, 133-142, 2016
74 2016 Spatial and class structure regularized sparse representation graph for semi-supervised hyperspectral image classification Y Shao, N Sang, C Gao, L Ma
Pattern Recognition 81, 81-94, 2018
72 2018 Class-wise distribution adaptation for unsupervised classification of hyperspectral remote sensing images Z Liu, L Ma, Q Du
IEEE Transactions on Geoscience and Remote Sensing 59 (1), 508-521, 2020
70 2020 Confident learning-based domain adaptation for hyperspectral image classification Z Fang, Y Yang, Z Li, W Li, Y Chen, L Ma, Q Du
IEEE Transactions on Geoscience and Remote Sensing 60, 1-16, 2022
53 2022 Non-rigid point set registration via coherent spatial mapping J Chen, J Ma, C Yang, L Ma, S Zheng
Signal Processing 106, 62-72, 2015
48 2015 Probabilistic class structure regularized sparse representation graph for semi-supervised hyperspectral image classification Y Shao, N Sang, C Gao, L Ma
Pattern recognition 63, 102-114, 2017
44 2017 Class centroid alignment based domain adaptation for classification of remote sensing images L Zhu, L Ma
Pattern Recognition Letters 83, 124-132, 2016
42 2016 Generalised supervised local tangent space alignment for hyperspectral image classification L Ma, MM Crawford, JW Tian
Electronics Letters 46 (7), 1, 2010
41 2010 Joint correlation alignment-based graph neural network for domain adaptation of multitemporal hyperspectral remote sensing images W Wang, L Ma, M Chen, Q Du
IEEE Journal of Selected Topics in Applied Earth Observations and Remote …, 2021
37 2021 Class-wise fully convolutional network for semantic segmentation of remote sensing images T Tian, Z Chu, Q Hu, L Ma
Remote Sensing 13 (16), 3211, 2021
31 2021 Manifold regularized distribution adaptation for classification of remote sensing images C Luo, L Ma
IEEE Access 6, 4697-4708, 2018
28 2018 Anomaly detection for hyperspectral images using local tangent space alignment L Ma, MM Crawford, J Tian
2010 IEEE International Geoscience and Remote Sensing Symposium, 824-827, 2010
27 2010 Supervised contrastive learning-based unsupervised domain adaptation for hyperspectral image classification Z Li, Q Xu, L Ma, Z Fang, Y Wang, W He, Q Du
IEEE Transactions on Geoscience and Remote Sensing, 2023
26 2023 
Jinwen Tian (田金文)Professor, School of Automation, Huazhong University of Science and Technologyhust.edu.cn üzerinde doğrulanmış e-posta adresine sahip