Folgen
Lichao Mou
Lichao Mou
German Aerospace Center (DLR), Technical University of Munich (TUM)
Bestätigte E-Mail-Adresse bei dlr.de - Startseite
Titel
Zitiert von
Zitiert von
Jahr
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
31782017
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
14312017
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
5742019
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
3652016
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
3282018
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
3242021
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
3102018
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
2442020
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
2392015
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
2372018
Self-supervised learning in remote sensing: A review
Y Wang, CM Albrecht, NAA Braham, L Mou, XX Zhu
IEEE Geoscience and Remote Sensing Magazine 10 (4), 213-247, 2022
2322022
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
2142019
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
2082018
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
2062019
Semi-supervised multitask learning for scene recognition
X Lu, X Li, L Mou
IEEE Transactions on Cybernetics 45 (9), 1967-1976, 2015
1992015
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
1922018
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
1782019
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
1772020
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
1582019
IM2HEIGHT: Height estimation from single monocular imagery via fully residual convolutional-deconvolutional network
L Mou, XX Zhu
arXiv preprint arXiv:1802.10249, 2018
1472018
Das System kann den Vorgang jetzt nicht ausführen. Versuchen Sie es später erneut.
Artikel 1–20