| 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 | 2826 | 2017 |
| Target classification using the deep convolutional networks for SAR images S Chen, H Wang, F Xu, YQ Jin IEEE transactions on geoscience and remote sensing 54 (8), 4806-4817, 2016 | 1311 | 2016 |
| Complex-valued convolutional neural network and its application in polarimetric SAR image classification Z Zhang, H Wang, F Xu, YQ Jin IEEE Transactions on Geoscience and Remote Sensing 55 (12), 7177-7188, 2017 | 608 | 2017 |
| Polarimetric SAR image classification using deep convolutional neural networks Y Zhou, H Wang, F Xu, YQ Jin IEEE Geoscience and Remote Sensing Letters 13 (12), 1935-1939, 2016 | 478 | 2016 |
| FAIR1M: A benchmark dataset for fine-grained object recognition in high-resolution remote sensing imagery X Sun, P Wang, Z Yan, F Xu, R Wang, W Diao, J Chen, J Li, Y Feng, T Xu, ... ISPRS Journal of Photogrammetry and Remote Sensing 184, 116-130, 2022 | 263 | 2022 |
| 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 | 252 | 2021 |
| In situ SST Quality Monitor (iQuam) F Xu, A Ignatov Journal of Atmospheric and Oceanic Technology 31 (1), 164-180, 2014 | 200 | 2014 |
| Deorientation theory of polarimetric scattering targets and application to terrain surface classification F Xu, YQ Jin IEEE Transactions on Geoscience and Remote Sensing 43 (10), 2351-2364, 2005 | 191 | 2005 |
| FUSAR-Ship: Building a high-resolution SAR-AIS matchup dataset of Gaofen-3 for ship detection and recognition X Hou, W Ao, Q Song, J Lai, H Wang, F Xu Science China Information Sciences 63, 1-19, 2020 | 175 | 2020 |
| Bidirectional analytic ray tracing for fast computation of composite scattering from electric-large target over a randomly rough surface F Xu, YQ Jin IEEE Transactions on Antennas and Propagation 57 (5), 1495-1505, 2009 | 168 | 2009 |
| Automatic reconstruction of building objects from multiaspect meter-resolution SAR images F Xu, YQ Jin IEEE Transactions on Geoscience and Remote Sensing 45 (7), 2336-2353, 2007 | 162 | 2007 |
| Application of deep-learning algorithms to MSTAR data H Wang, S Chen, F Xu, YQ Jin 2015 IEEE International Geoscience and Remote Sensing Symposium (IGARSS …, 2015 | 126 | 2015 |
| Imaging simulation of polarimetric SAR for a comprehensive terrain scene using the mapping and projection algorithm F Xu, YQ Jin IEEE Transactions on Geoscience and Remote Sensing 44 (11), 3219-3234, 2006 | 123 | 2006 |
| Detection and discrimination of ship targets in complex background from spaceborne ALOS-2 SAR images W Ao, F Xu, Y Li, H Wang IEEE Journal of Selected Topics in Applied Earth Observations and Remote …, 2018 | 120 | 2018 |
| Deep learning as applied in SAR target recognition and terrain classification X Feng, W Haipeng, J Yaqiu 雷达学报 6 (2), 136-148, 2017 | 103 | 2017 |
| An active deep learning approach for minimally supervised PolSAR image classification H Bi, F Xu, Z Wei, Y Xue, Z Xu IEEE Transactions on Geoscience and Remote Sensing 57 (11), 9378-9395, 2019 | 96 | 2019 |
| Polarimetric scattering and SAR information retrieval YQ Jin, F Xu John Wiley & Sons, 2013 | 83 | 2013 |
| A backscattering model of rainfall over rough sea surface for synthetic aperture radar F Xu, X Li, P Wang, J Yang, WG Pichel, YQ Jin IEEE Transactions on Geoscience and Remote Sensing 53 (6), 3042-3054, 2014 | 78 | 2014 |
| Deep learning in remote sensing: a comprehensive review and list of resources. IEEE Geosci. Remote Sens. Mag. 5, 8–36 XX Zhu, D Tuia, L Mou, GS Xia, L Zhang, F Xu, F Fraundorfer | 75 | 2017 |
| Needles in a haystack: Tracking city-scale moving vehicles from continuously moving satellite W Ao, Y Fu, X Hou, F Xu IEEE Transactions on Image Processing 29, 1944-1957, 2019 | 73 | 2019 |
Ya-Qiu JinFudan University在 fudan.edu.cn 的电子邮件经过验证
