Zobrazeno 1 - 10
of 6 468
pro vyhledávání: '"Luo,Ying"'
Autor:
Bartoszek, Krzysztof, Luo, Ying
Publikováno v:
Mathematica Applicanda (Matematyka Stosowana) 51(2): 183-198, 2023
Visualizing data through Czekanowski's diagram has as its aim the illustration of the relationships between objects. Often, obvious clusters of observations are directly visible. However, it is not straightforward to precisely delineate these cluster
Externí odkaz:
http://arxiv.org/abs/2412.19679
Reinforcement learning (RL) policies are prone to high-frequency oscillations, especially undesirable when deploying to hardware in the real-world. In this paper, we identify, categorize, and compare methods from the literature that aim to mitigate h
Externí odkaz:
http://arxiv.org/abs/2410.16632
We propose the expert composer policy, a framework to reliably expand the skill repertoire of quadruped agents. The composer policy links pair of experts via transitions to a sampled target state, allowing experts to be composed sequentially. Each ex
Externí odkaz:
http://arxiv.org/abs/2403.11412
Autor:
Yu Cheng, Wen-Jing Song, Mei-Ting Huang, Yuan Gao, Luo-Ying Xie, Ying-Si Li, Song-Lin Yang, Xiao-Ming Yan
Publikováno v:
International Journal of Ophthalmology, Vol 17, Iss 11, Pp 2014-2022 (2024)
AIM: To investigate the efficacy and mechanisms of indirect intense pulsed light (IPL) irradiation on meibomian gland dysfunction (MGD). METHODS: A total of 60 MGD patients was included in this prospective randomized controlled trial. Patients were r
Externí odkaz:
https://doaj.org/article/b5b3dbebb33e4aac82e1e6f2283f7d61
Publikováno v:
Data Technologies and Applications, 2024, Vol. 58, Issue 5, pp. 838-857.
Externí odkaz:
http://www.emeraldinsight.com/doi/10.1108/DTA-06-2023-0230
This paper proposes the transition-net, a robust transition strategy that expands the versatility of robot locomotion in the real-world setting. To this end, we start by distributing the complexity of different gaits into dedicated locomotion policie
Externí odkaz:
http://arxiv.org/abs/2306.08224
Autor:
Huang, Po-Hsuan, Pan, Yi-Hsiang, Luo, Ying-Sheng, Chen, Yi-Fan, Lo, Yu-Cheng, Chen, Trista Pei-Chun, Perng, Cherng-Kang
This paper presents a deep learning-based wound classification tool that can assist medical personnel in non-wound care specialization to classify five key wound conditions, namely deep wound, infected wound, arterial wound, venous wound, and pressur
Externí odkaz:
http://arxiv.org/abs/2303.16522
Autor:
Luo, Ying1,2,3 (AUTHOR), Jia, Xiaoli1,2,3 (AUTHOR), Wu, Xiaozhuo4 (AUTHOR), Diao, Ling1 (AUTHOR), Zhao, Yawei5 (AUTHOR), Liu, Xing1,2,3 (AUTHOR), Peng, Yi1,2,3 (AUTHOR), Zhong, Wen5 (AUTHOR), Xing, Malcolm4 (AUTHOR) malcolm.xing@umanitoba.ca, Lyu, Guozhong1,2,3,6 (AUTHOR) luguozhong@jiangnan.edu.cn
Publikováno v:
Journal of Nanobiotechnology. 12/19/2024, p1-18. 18p.