| A normalized Gaussian Wasserstein distance for tiny object detection J Wang, C Xu, W Yang, L Yu arXiv preprint arXiv:2110.13389, 2021 | 424 | 2021 |
| Sliding modes after the first decade of the 21st century L Fridman, J Moreno, R Iriarte Lecture notes in control and information sciences 412, 113-149, 2011 | 294 | 2011 |
| Compressive sensing with chaotic sequence L Yu, JP Barbot, G Zheng, H Sun IEEE Signal Processing Letters 17 (8), 731-734, 2010 | 246 | 2010 |
| Bayesian compressive sensing for cluster structured sparse signals L Yu, H Sun, JP Barbot, G Zheng Signal Processing, 2012 | 223 | 2012 |
| RFLA: Gaussian receptive field based label assignment for tiny object detection C Xu, J Wang, W Yang, H Yu, L Yu, GS Xia European conference on computer vision, 526-543, 2022 | 166 | 2022 |
| Detecting tiny objects in aerial images: A normalized Wasserstein distance and a new benchmark C Xu, J Wang, W Yang, H Yu, L Yu, GS Xia ISPRS Journal of Photogrammetry and Remote Sensing 190, 79-93, 2022 | 152 | 2022 |
| Event enhanced high-quality image recovery B Wang, J He, L Yu, GS Xia, W Yang Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23 …, 2020 | 129 | 2020 |
| Dot distance for tiny object detection in aerial images C Xu, J Wang, W Yang, L Yu Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2021 | 113 | 2021 |
| Motion deblurring with real events F Xu, L Yu, B Wang, W Yang, GS Xia, X Jia, Z Qiao, J Liu ICCV, 2583-2592, 2021 | 104 | 2021 |
| Unifying motion deblurring and frame interpolation with events X Zhang, L Yu Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 90 | 2022 |
| GLF-CR: SAR-enhanced cloud removal with global–local fusion F Xu, Y Shi, P Ebel, L Yu, GS Xia, W Yang, XX Zhu ISPRS Journal of Photogrammetry and Remote Sensing 192, 268-278, 2022 | 78 | 2022 |
| Compressive sensing for cluster structured sparse signals: variational bayes approach L Yu, JP Barbot, G Zheng, H Sun IET Signal Processing 10 (7), 770-779, 2016 | 72 | 2016 |
| Dynamic coarse-to-fine learning for oriented tiny object detection C Xu, J Ding, J Wang, W Yang, H Yu, L Yu, GS Xia Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023 | 70 | 2023 |
| Det: A high-resolution dvs dataset for lane extraction W Cheng, H Luo, W Yang, L Yu, S Chen, W Li Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2019 | 66 | 2019 |
| Dynamical sparse recovery with finite-time convergence L Yu, G Zheng, JP Barbot IEEE Transactions on Signal Processing 65 (23), 6146-6157, 2017 | 61 | 2017 |
| Compressive sensing matrix designed by tent map, for secure data transmission M Frunzete, L Yu, JP Barbot, A Vlad Signal Processing Algorithms, Architectures, Arrangements, and Applications …, 2011 | 59 | 2011 |
| Toeplitz-structured chaotic sensing matrix for compressive sensing L Yu, JP Barbot, G Zheng, H Sun 2010 7th International Symposium on Communication Systems, Networks …, 2010 | 44 | 2010 |
| Model based Bayesian compressive sensing via local beta process L Yu, H Sun, G Zheng, JP Barbot Signal Processing 108, 259-271, 2015 | 40 | 2015 |
| Event-based Synthetic Aperture Imaging with a Hybrid Network X Zhang, W Liao, L Yu, W Yang, GS Xia CVPR 2021 (Oral), 14235-14244, 2021 | 36 | 2021 |
| Frequency estimation of multiple sinusoids with three sub-Nyquist channels S Huang, H Zhang, H Sun, L Yu, L Chen Signal Processing 139, 96-101, 2017 | 34 | 2017 |
