Zobrazeno 1 - 10
of 152
pro vyhledávání: '"Chen, Shaokang"'
Autor:
Wu, Qiang, Yang, Qianhui, Fang, Chaoyin, Wang, Yu, Chen, Xiaoyue, Wen, Xishan, Lan, Lei, Deng, Yeqiang, Xu, Jun, Chen, Shaokang
Publikováno v:
In Electric Power Systems Research June 2024 231
The effectiveness of Symmetric Positive Definite (SPD) manifold features has been proven in various computer vision tasks. However, due to the non-Euclidean geometry of these features, existing Euclidean machineries cannot be directly used. In this p
Externí odkaz:
http://arxiv.org/abs/1806.05343
This work shows that it is possible to fool/attack recent state-of-the-art face detectors which are based on the single-stage networks. Successfully attacking face detectors could be a serious malware vulnerability when deploying a smart surveillance
Externí odkaz:
http://arxiv.org/abs/1712.08263
Publikováno v:
Water Supply, Vol 22, Iss 6, Pp 5771-5784 (2022)
When a traditional Weakly-Compressible Smoothed Particle Hydrodynamics (WCSPH) model is used to simulate free surface flow with a large Reynolds number, an unstable numerical calculation due to high random pressure oscillations will result, while an
Externí odkaz:
https://doaj.org/article/22ce03b612534dee9f71b601f80df59b
Autor:
Zhang, Zhaohui, Chen, Shaokang
Publikováno v:
In Continental Shelf Research 1 October 2022 248
Autor:
Zhao, Taolin, Shen, Jiangang, Meng, Yu, Huang, Xiyun, Chen, Shaokang, Zheng, Yingdi, Chang, Liyao
Publikováno v:
In Journal of Alloys and Compounds 15 July 2022 909
Publikováno v:
In Composites Part A March 2022 154
Autor:
Fu, Zhiwei, Huang, Youcong, Zheng, Zhongnan, Zhang, Ying, Xu, Jun, Chen, Shaokang, Zhang, Hao
Publikováno v:
Journal of Materials Engineering & Performance; Oct2024, Vol. 33 Issue 19, p10645-10662, 18p
Autor:
Zhang, Yanni, Shu, Pan, Zhai, Fangyan, Chen, Shaokang, Wang, Kai, Deng, Jun, Kang, Furu, Li, Lele
Publikováno v:
In Process Safety and Environmental Protection August 2021 152:536-548
Automatic attribute discovery methods have gained in popularity to extract sets of visual attributes from images or videos for various tasks. Despite their good performance in some classification tasks, it is difficult to evaluate whether the attribu
Externí odkaz:
http://arxiv.org/abs/1610.04957