| Deep convolutional neural networks for hyperspectral image classification W Hu, Y Huang, L Wei, F Zhang, H Li Journal of Sensors 2015 (1), 258619, 2015 | 1937 | 2015 |
| Hyperspectral image classification using deep pixel-pair features W Li, G Wu, F Zhang, Q Du IEEE Transactions on Geoscience and Remote Sensing 55 (2), 844-853, 2016 | 827 | 2016 |
| DeepUNet: A deep fully convolutional network for pixel-level sea-land segmentation R Li, W Liu, L Yang, S Sun, W Hu, F Zhang, W Li IEEE journal of selected topics in applied earth observations and remote
, 2018 | 392 | 2018 |
| TreeUNet: Adaptive tree convolutional neural networks for subdecimeter aerial image segmentation K Yue, L Yang, R Li, W Hu, F Zhang, W Li ISPRS Journal of Photogrammetry and Remote Sensing 156, 1-13, 2019 | 158 | 2019 |
| Collaborative-representation-based nearest neighbor classifier for hyperspectral imagery W Li, Q Du, F Zhang, W Hu IEEE Geoscience and Remote Sensing Letters 12 (2), 389-393, 2014 | 126 | 2014 |
| Multi-aspect-aware bidirectional LSTM networks for synthetic aperture radar target recognition F Zhang, C Hu, Q Yin, W Li, HC Li, W Hong Ieee Access 5, 26880-26891, 2017 | 91 | 2017 |
| Noise-tolerant paradigm for training face recognition CNNs W Hu, Y Huang, F Zhang, R Li Proceedings of the IEEE/CVF conference on computer vision and pattern
, 2019 | 86 | 2019 |
| Multiple mode SAR raw data simulation and parallel acceleration for Gaofen-3 mission F Zhang, X Yao, H Tang, Q Yin, Y Hu, B Lei IEEE Journal of Selected Topics in Applied Earth Observations and Remote
, 2018 | 81 | 2018 |
| Graph-based few-shot learning with transformed feature propagation and optimal class allocation R Zhang, S Yang, Q Zhang, L Xu, Y He, F Zhang Neurocomputing 470, 247-256, 2022 | 73 | 2022 |
| Hyperspectral image classification by fusing collaborative and sparse representations W Li, Q Du, F Zhang, W Hu IEEE Journal of Selected Topics in Applied Earth Observations and Remote
, 2016 | 72 | 2016 |
| SAR target small sample recognition based on CNN cascaded features and AdaBoost rotation forest F Zhang, Y Wang, J Ni, Y Zhou, W Hu IEEE Geoscience and Remote Sensing Letters 17 (6), 1008-1012, 2019 | 71 | 2019 |
| A sidelobe-aware small ship detection network for synthetic aperture radar imagery Y Zhou, H Liu, F Ma, Z Pan, F Zhang IEEE Transactions on Geoscience and Remote Sensing 61, 1-16, 2023 | 68 | 2023 |
| Fast task-specific region merging for SAR image segmentation F Ma, F Zhang, D Xiang, Q Yin, Y Zhou IEEE Transactions on Geoscience and Remote Sensing 60, 1-16, 2022 | 63 | 2022 |
| Accelerating time-domain SAR raw data simulation for large areas using multi-GPUs F Zhang, C Hu, W Li, W Hu, HC Li IEEE Journal of selected topics in applied earth observations and remote
, 2014 | 61 | 2014 |
| Multiple features learning for ship classification in optical imagery L Huang, W Li, C Chen, F Zhang, H Lang Multimedia Tools and Applications 77, 13363-13389, 2018 | 56 | 2018 |
| What catch your attention in SAR images: Saliency detection based on soft-superpixel lacunarity cue F Ma, X Sun, F Zhang, Y Zhou, HC Li IEEE Transactions on Geoscience and Remote Sensing 61, 1-17, 2022 | 54 | 2022 |
| Hyperspectral dimensionality reduction by tensor sparse and low-rank graph-based discriminant analysis L Pan, HC Li, YJ Deng, F Zhang, XD Chen, Q Du Remote Sensing 9 (5), 452, 2017 | 54 | 2017 |
| Fast SAR image segmentation with deep task-specific superpixel sampling and soft graph convolution F Ma, F Zhang, Q Yin, D Xiang, Y Zhou IEEE Transactions on Geoscience and Remote Sensing 60, 1-16, 2021 | 52 | 2021 |
| Deep CNN with multi-scale rotation invariance features for ship classification Q Shi, W Li, F Zhang, W Hu, X Sun, L Gao Ieee Access 6, 38656-38668, 2018 | 50 | 2018 |
| Slim and efficient neural network design for resource-constrained SAR target recognition H Chen, F Zhang, B Tang, Q Yin, X Sun Remote Sensing 10 (10), 1618, 2018 | 48 | 2018 |
Wei HuComputer Science Department, Beijing University of Chemical TechnologyPatvirtintas el. paštas mail.buct.edu.cn
