Zobrazeno 1 - 10
of 219
pro vyhledávání: '"Zhu Anqi"'
Autor:
Zhu Anqi
Publikováno v:
Applied Mathematics and Nonlinear Sciences, Vol 9, Iss 1 (2024)
The evolving times, along with the advancements in science and technology, have led to a transformation in public art. The emergence of digital media public art, which plays a crucial role in shaping the city’s image, has brought art to life. This
Externí odkaz:
https://doaj.org/article/5493d0d91fa14e42984c06cddc3e8d16
While remarkable progress has been made on supervised skeleton-based action recognition, the challenge of zero-shot recognition remains relatively unexplored. In this paper, we argue that relying solely on aligning label-level semantics and global sk
Externí odkaz:
http://arxiv.org/abs/2406.13327
Human action recognition is crucial in computer vision systems. However, in real-world scenarios, human actions often fall outside the distribution of training data, requiring a model to both recognize in-distribution (ID) actions and reject out-of-d
Externí odkaz:
http://arxiv.org/abs/2405.20633
Publikováno v:
E3S Web of Conferences, Vol 165, p 03015 (2020)
In order to study the energy characteristics of limestone under different initial confining pressures and different unloading rates, based on MTS815 flex test GT rock mechanics test system and acoustic emission (AE) 3D positioning real-time monitorin
Externí odkaz:
https://doaj.org/article/c38684c23c0f49f2b12fbd825bdf9e39
Autor:
Ren, Hongze1,2 (AUTHOR), Zhu, Anqi3 (AUTHOR), Yang, Wei4 (AUTHOR), Jia, Yiwen1 (AUTHOR), Cheng, Hui1 (AUTHOR), Wu, Ye1,2 (AUTHOR), Tang, Zhengqi1 (AUTHOR), Ye, Weifan1 (AUTHOR), Sun, Mayu5 (AUTHOR), Xie, Yujie1,2 (AUTHOR) xieyj@shu.edu.cn, Yu, Meihua1 (AUTHOR) myu@shu.edu.cn, Chen, Yu1,2 (AUTHOR) chenyuedu@shu.edu.cn
Publikováno v:
Advanced Science. 10/28/2024, Vol. 11 Issue 40, p1-20. 20p.
Skeleton-based action recognition receives increasing attention because the skeleton representations reduce the amount of training data by eliminating visual information irrelevant to actions. To further improve the sample efficiency, meta-learning-b
Externí odkaz:
http://arxiv.org/abs/2209.10073
Autor:
Wang, Xihui1 (AUTHOR), Zhu, Anqi2 (AUTHOR), Fan, Yu1 (AUTHOR) fanyu@ustc.edu.cn, Liang, Liang2 (AUTHOR)
Publikováno v:
International Journal of Production Research. Jul2024, Vol. 62 Issue 14, p5211-5235. 25p.
Autor:
Yang, Xiaomeng, Xu, Fanglei, Qin, Keyi, Yu, Yida, Zheng, Qishan, Zhu, Anqi, Hu, Biying, Gu, Chuanhua
Publikováno v:
In Thinking Skills and Creativity December 2024 54
Publikováno v:
In Biochemical Pharmacology January 2025 231
Autor:
Dorighi, Kristel M., Zhu, Anqi, Fortin, Jean-Philippe, Hung-Hao Lo, Jerry, Sudhamsu, Jawahar, Wendorff, Timothy J., Durinck, Steffen, Callow, Marinella, Foster, Scott A., Haley, Benjamin
Publikováno v:
In Cell Reports 25 June 2024 43(6)