Lichao Mou

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Xiao Xiang ZhuTechnical University of MunichVerified email at tum.de
Yuansheng HuaSignal Processing in Earth Observation, Technical University of Munich (TUM) & Remote Sensing Technology Institute (IMF), German Aerospace Center (DLR)Verified email at dlr.de
Gui-Song XiaProfessor of Computer Science, Wuhan University, ChinaVerified email at whu.edu.cn
Michael SchmittBundeswehr University MunichVerified email at unibw.de
Devis TuiaEcole Polytechnique Fédérale de Lausanne (EPFL)Verified email at epfl.ch
Pedram GhamisiHZDR & IARAI, Group Leader and Research ProfessorVerified email at hzdr.de
Yuanyuan WangTechnical University of Munich & German Aerospace CenterVerified email at tum.de
Feng Xu (徐丰)Fudan UniversityVerified email at fudan.edu.cn
Lorenzo BruzzoneProfessor of Telecommunications, University of TrentoVerified email at ing.unitn.it
xiaoqiang LuXi’an Institute of Optics and Precision Mechanics, Chinese Academy of SciencesVerified email at opt.ac.cn
Pu JinRemote Sensing Technology Institute (IMF), German Aerospace Center (DLR)Verified email at dlr.de
zhang liangpeiProfessor, Wuhan UniversityVerified email at whu.edu.cn
Yilei ShiChair of Remote Sensing Technology, Technical University of MunichVerified email at tum.de
Konrad HeidlerTechnische Universität München (TUM)Verified email at tum.de
Sudipan SahaIndian Institute of Technology DelhiVerified email at scai.iitd.ac.in
Friedrich FraundorferProfessor, TU GrazVerified email at icg.tugraz.at
Xuelong LiProfessor, Northwestern Polytechnical University, ChinaVerified email at ieee.org
Francesca BovoloTrento-Fondazione Bruno Kessler (FBK)Verified email at fbk.eu
Jingliang HuTechnical University of Munich (TUM) & German Aerospace Center (DLR)Verified email at tum.de
Lloyd HughesEcole Polytechnique Fédérale de Lausanne (EPFL), ECEO, SwitzerlandVerified email at epfl.ch

Lichao Mou

German Aerospace Center (DLR), Technical University of Munich (TUM)

Verified email at dlr.de - Homepage

Remote Sensing Computer Vision Deep Learning AI4EO


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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	2241	2017
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	983	2017
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	379	2019
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	292	2016
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	241	2018
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	229	2018
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	214	2015
Semi-supervised multitask learning for scene recognition X Lu, X Li, L Mou IEEE Transactions on Cybernetics 45 (9), 1967-1976, 2015	177	2015
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	169	2018
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	165	2019
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	156	2018
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	148	2019
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	147	2018
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	142	2021
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	138	2020
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	129	2019
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	105	2019
IM2HEIGHT: Height estimation from single monocular imagery via fully residual convolutional-deconvolutional network L Mou, XX Zhu arXiv preprint arXiv:1802.10249, 2018	104	2018
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	100	2019
Relation matters: Relational context-aware fully convolutional network for semantic segmentation of high-resolution aerial images L Mou, Y Hua, XX Zhu IEEE Transactions on Geoscience and Remote Sensing 58 (11), 7557-7569, 2020	89	2020

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