| An interpretable mortality prediction model for COVID-19 patients L Yan, HT Zhang, J Goncalves, Y Xiao, M Wang, Y Guo, C Sun, X Tang, ... Nature machine intelligence 2 (5), 283-288, 2020 | 1009 | 2020 |
| Prediction of criticality in patients with severe Covid-19 infection using three clinical features: a machine learning-based prognostic model with clinical data in Wuhan L Yan, HT Zhang, Y Xiao, M Wang, Y Guo, C Sun, X Tang, L Jing, S Li, ... MedRxiv, 2020.02. 27.20028027, 2020 | 344 | 2020 |
| Multi-spectral remote image registration based on SIFT Z Yi, C Zhiguo, X Yang Electronics Letters 44 (2), 1, 2008 | 278 | 2008 |
| TasselNet: counting maize tassels in the wild via local counts regression network H Lu, Z Cao, Y Xiao, B Zhuang, C Shen Plant methods 13, 1-17, 2017 | 268 | 2017 |
| A fast and robust local descriptor for 3D point cloud registration J Yang, Z Cao, Q Zhang Information Sciences 346, 163-179, 2016 | 239 | 2016 |
| Monocular relative depth perception with web stereo data supervision K Xian, C Shen, Z Cao, H Lu, Y Xiao, R Li, Z Luo Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2018 | 229 | 2018 |
| A machine learning-based model for survival prediction in patients with severe COVID-19 infection L Yan, H Zhang, J Goncalves, Y Xiao, M Wang, Y Guo, C Sun, X Tang, ... | 200 | 2020 |
| From open set to closed set: Counting objects by spatial divide-and-conquer H Xiong, H Lu, C Liu, L Liu, Z Cao, C Shen Proceedings of the IEEE/CVF international conference on computer vision …, 2019 | 200 | 2019 |
| A2j: Anchor-to-joint regression network for 3d articulated pose estimation from a single depth image F Xiong, B Zhang, Y Xiao, Z Cao, T Yu, JT Zhou, J Yuan Proceedings of the IEEE/CVF International Conference on Computer Vision, 793-802, 2019 | 198 | 2019 |
| Structure-guided ranking loss for single image depth prediction K Xian, J Zhang, O Wang, L Mai, Z Lin, Z Cao Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020 | 194 | 2020 |
| Automatic image-based detection technology for two critical growth stages of maize: Emergence and three-leaf stage Z Yu, Z Cao, X Wu, X Bai, Y Qin, W Zhuo, Y Xiao, X Zhang, H Xue Agricultural and forest meteorology 174, 65-84, 2013 | 171 | 2013 |
| TOLDI: An effective and robust approach for 3D local shape description J Yang, Q Zhang, Y Xiao, Z Cao Pattern Recognition 65, 175-187, 2017 | 167 | 2017 |
| P2b: Point-to-box network for 3d object tracking in point clouds H Qi, C Feng, Z Cao, F Zhao, Y Xiao Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2020 | 159 | 2020 |
| Crop segmentation from images by morphology modeling in the CIE L* a* b* color space XD Bai, ZG Cao, Y Wang, ZH Yu, XF Zhang, CN Li Computers and electronics in agriculture 99, 21-34, 2013 | 148 | 2013 |
| Interior attention-aware network for infrared small target detection K Wang, S Du, C Liu, Z Cao IEEE Transactions on Geoscience and Remote Sensing 60, 1-13, 2022 | 133 | 2022 |
| NM-Net: Mining reliable neighbors for robust feature correspondences C Zhao, Z Cao, C Li, X Li, J Yang Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2019 | 133 | 2019 |
| TasselNetv2: in-field counting of wheat spikes with context-augmented local regression networks H Xiong, Z Cao, H Lu, S Madec, L Liu, C Shen Plant methods 15 (1), 150, 2019 | 131 | 2019 |
| Action recognition for depth video using multi-view dynamic images Y Xiao, J Chen, Y Wang, Z Cao, JT Zhou, X Bai Information Sciences 480, 287-304, 2019 | 123 | 2019 |
| Deep attention-based classification network for robust depth prediction R Li, K Xian, C Shen, Z Cao, H Lu, L Hang Computer Vision–ACCV 2018: 14th Asian Conference on Computer Vision, Perth …, 2019 | 120 | 2019 |
| In-field automatic observation of wheat heading stage using computer vision Y Zhu, Z Cao, H Lu, Y Li, Y Xiao Biosystems Engineering 143, 28-41, 2016 | 118 | 2016 |
Yang Xiao (肖阳)Huazhong University of Science and TechnologyVerified email at hust.edu.cn
