Lichao Mou

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Xiao Xiang ZhuProfessor for Data Science in Earth Observation, TUM & Department Head "EO Data Science", DLRVerified 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
Pedram GhamisiHelmholtz-Zentrum Dresden-Rossendorf, Division Exploration, Machine Learning Group (head)Verified email at hzdr.de
Michael SchmittBundeswehr University MunichVerified email at unibw.de
Devis TuiaEcole Polytechnique Fédérale de Lausanne (EPFL)Verified email at epfl.ch
Feng Xu (徐丰)Fudan UniversityVerified email at fudan.edu.cn
xiaoqiang LuXi’an Institute of Optics and Precision Mechanics, Chinese Academy of SciencesVerified email at opt.ac.cn
Yuanyuan WangDepartment of EO Data Science, German Aerospace CenterVerified email at tum.de
Gui-Song XiaProfessor of Computer Science, Wuhan University, ChinaVerified email at whu.edu.cn
Lorenzo BruzzoneProfessor of Telecommunications, University of TrentoVerified email at ing.unitn.it
Xuelong LiProfessor, Northwestern Polytechnical University, ChinaVerified email at ieee.org
Friedrich FraundorferAssociate Professor, TU GrazVerified email at icg.tugraz.at
zhang liangpeiProfessor, Wuhan UniversityVerified email at whu.edu.cn
Yilei ShiChair of Remote Sensing Technology, Technical University of MunichVerified email at tum.de
Haiying HuangTechnische Universitaet MünchenVerified email at tum.de
Qingpeng LiBeihang UniversityVerified email at buaa.edu.cn
Jingliang HuTechnical University of Munich (TUM) & German Aerospace Center (DLR)Verified email at tum.de
Hui LuTsinghua UniversityVerified email at tsinghua.edu.cn
Lloyd HughesTechnical University of MunichVerified email at tum.de
Yiming Jiang (姜一鸣)Helmholtz Zentrum München/ Technische Universitaet München/Lanzhou UniversityVerified email at helmholtz-muenchen.de

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	1338	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	584	2017
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	209	2016
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	203	2019
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	185	2015
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	173	2018
Semi-supervised multitask learning for scene recognition X Lu, X Li, L Mou IEEE Transactions on Cybernetics 45 (9), 1967-1976, 2015	157	2015
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	107	2018
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	94	2018
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	93	2018
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	88	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	82	2019
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	75	2019
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	66	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	65	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	63	2019
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	60	2019
Multitemporal very high resolution from space: Outcome of the 2016 IEEE GRSS data fusion contest L Mou, X Zhu, M Vakalopoulou, K Karantzalos, N Paragios, B Le Saux, ... IEEE Journal of Selected Topics in Applied Earth Observations and Remote …, 2017	53	2017
FusioNet: A two-stream convolutional neural network for urban scene classification using PolSAR and hyperspectral data J Hu, L Mou, A Schmitt, XX Zhu 2017 Joint Urban Remote Sensing Event (JURSE), 1-4, 2017	52	2017
IM2HEIGHT: Height estimation from single monocular imagery via fully residual convolutional-deconvolutional network L Mou, XX Zhu arXiv preprint arXiv:1802.10249, 2018	51	2018

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