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Lichao Mou
Lichao Mou
German Aerospace Center (DLR), Technical University of Munich (TUM)
Verified email at dlr.de - Homepage
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Cited by
Year
Deep learning in remote sensing: A comprehensive review and list of resources
XX Zhu, D Tuia, L Mou, GS Xia, L Zhang, F Xu, F Fraundorfer
IEEE geoscience and remote sensing magazine 5 (4), 8-36, 2017
20842017
Deep recurrent neural networks for hyperspectral image classification
L Mou, P Ghamisi, XX Zhu
IEEE Transactions on Geoscience and Remote Sensing 55 (7), 3639-3655, 2017
9002017
Learning spectral-spatial-temporal features via a recurrent convolutional neural network for change detection in multispectral imagery
L Mou, L Bruzzone, XX Zhu
IEEE Transactions on Geoscience and Remote Sensing, 2019
3452019
Learning a transferable change rule from a recurrent neural network for land cover change detection
H Lyu, H Lu, L Mou
Remote Sensing 8 (6), 506, 2016
2792016
Unsupervised spectral–spatial feature learning via deep residual Conv–Deconv network for hyperspectral image classification
L Mou, P Ghamisi, XX Zhu
IEEE Transactions on Geoscience and Remote Sensing 56 (1), 391-406, 2018
2272018
Scene recognition by manifold regularized deep learning architecture
Y Yuan, L Mou, X Lu
IEEE Transactions on Neural Networks and Learning Systems 26 (10), 2222-2233, 2015
2052015
Long-term and high-concentration heavy-metal contamination strongly influences the microbiome and functional genes in Yellow River sediments
Y Chen, Y Jiang, H Huang, L Mou, J Ru, J Zhao, S Xiao
Science of the Total Environment 637, 1400-1412, 2018
2042018
Semi-supervised multitask learning for scene recognition
X Lu, X Li, L Mou
IEEE Transactions on Cybernetics 45 (9), 1967-1976, 2015
1752015
Identifying corresponding patches in SAR and optical images with a pseudo-siamese CNN
LH Hughes, M Schmitt, L Mou, Y Wang, XX Zhu
IEEE Geoscience and Remote Sensing Letters 15 (5), 784-788, 2018
1532018
A Relation-Augmented Fully Convolutional Network for Semantic Segmentationin Aerial Scenes
L Mou, Y Hua, XX Zhu
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) 2019, 2019
1492019
HSF-Net: Multiscale deep feature embedding for ship detection in optical remote sensing imagery
Q Li, L Mou, Q Liu, Y Wang, XX Zhu
IEEE Transactions on Geoscience and Remote Sensing 56 (12), 7147-7161, 2018
1442018
Vehicle Instance Segmentation from Aerial Image and Video Using a Multi-Task Learning Residual Fully Convolutional Network
L Mou, XX Zhu
IEEE Transactions on Geoscience and Remote Sensing 56 (11), 6699-6711, 2018
1432018
Learning to pay attention on spectral domain: A spectral attention module-based convolutional network for hyperspectral image classification
L Mou, XX Zhu
IEEE Transactions on Geoscience and Remote Sensing 58 (1), 110-122, 2019
1362019
Deep learning meets SAR: Concepts, models, pitfalls, and perspectives
XX Zhu, S Montazeri, M Ali, Y Hua, Y Wang, L Mou, Y Shi, F Xu, R Bamler
IEEE Geoscience and Remote Sensing Magazine 9 (4), 143-172, 2021
1242021
Nonlocal Graph Convolutional Networks for Hyperspectral Image Classification
L Mou, X Lu, X Li, XX Zhu
IEEE Transactions on Geoscience and Remote Sensing 58 (12), 8246 - 8257, 2020
1242020
Recurrently exploring class-wise attention in a hybrid convolutional and bidirectional LSTM network for multi-label aerial image classification
Y Hua, L Mou, XX Zhu
ISPRS journal of photogrammetry and remote sensing 149, 188-199, 2019
1232019
Local climate zone-based urban land cover classification from multi-seasonal Sentinel-2 images with a recurrent residual network
C Qiu, L Mou, M Schmitt, XX Zhu
ISPRS Journal of Photogrammetry and Remote Sensing 154, 151-162, 2019
992019
IM2HEIGHT: Height estimation from single monocular imagery via fully residual convolutional-deconvolutional network
L Mou, XX Zhu
arXiv preprint arXiv:1802.10249, 2018
982018
R -Net: A Deep Network for Multi-oriented Vehicle Detection in Aerial Images and Videos
Q Li, L Mou, Q Xu, Y Zhang, XX Zhu
IEEE Transactions on Geoscience and Remote Sensing, 2019
922019
RiFCN: Recurrent network in fully convolutional network for semantic segmentation of high resolution remote sensing images
L Mou, XX Zhu
arXiv preprint arXiv:1805.02091, 2018
832018
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