| 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 | 3169 | 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 | 1425 | 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 | 571 | 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 | 365 | 2016 |
| 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 | 328 | 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 | 323 | 2021 |
| 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 | 309 | 2018 |
| 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 | 242 | 2020 |
| 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 | 239 | 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 | 235 | 2018 |
| 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 | 231 | 2022 |
| 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 | 213 | 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 | 208 | 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 | 206 | 2019 |
| Semi-supervised multitask learning for scene recognition X Lu, X Li, L Mou IEEE Transactions on Cybernetics 45 (9), 1967-1976, 2015 | 199 | 2015 |
| 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 | 192 | 2018 |
| 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 | 177 | 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 | 177 | 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 | 157 | 2019 |
| IM2HEIGHT: Height estimation from single monocular imagery via fully residual convolutional-deconvolutional network L Mou, XX Zhu arXiv preprint arXiv:1802.10249, 2018 | 147 | 2018 |
Xiao Xiang ZhuTechnical University of Munich在 tum.de 的电子邮件经过验证
