Zobrazeno 1 - 10
of 584
pro vyhledávání: '"CHEN Huili"'
Autor:
CHEN Huili, LI Jie
Publikováno v:
Gong-kuang zidonghua, Vol 46, Iss 4, Pp 109-112 (2020)
For problems of large output voltage ripple-wave and poor intrinsic safety performance existed in mine-used intrinsic safety type power supply caused by large filtering capacitor of switching converter, a filtering capacitor resolution scheme was pro
Externí odkaz:
https://doaj.org/article/4d269fc45efa46e98591f914628fecad
Publikováno v:
Proceedings of the 2024 ACM/IEEE International Conference on Human - Robot Interaction (HRI24), March 11 - 14, 2024, Boulder, CO, USA
In this paper, we introduce a novel conceptual model for a robot's behavioral adaptation in its long-term interaction with humans, integrating dynamic robot role adaptation with principles of flow experience from psychology. This conceptualization in
Externí odkaz:
http://arxiv.org/abs/2401.02833
This report presents a comprehensive study on deep learning models for brand logo classification in real-world scenarios. The dataset contains 3,717 labeled images of logos from ten prominent brands. Two types of models, Convolutional Neural Networks
Externí odkaz:
http://arxiv.org/abs/2305.12242
Autor:
Xie, Yiluo1,2 (AUTHOR), Chen, Huili3 (AUTHOR), Zhang, Xueying1 (AUTHOR), Zhang, Jing4 (AUTHOR), Zhang, Kai2 (AUTHOR), Wang, Xinyu2 (AUTHOR), Min, Shengping1 (AUTHOR), Wang, Xiaojing1 (AUTHOR) wangxiaojing8888@163.com, Lian, Chaoqun3 (AUTHOR) lianchaoqun@bbmc.edu.cn
Publikováno v:
Cancer Cell International. 11/23/2024, Vol. 24 Issue 1, p1-16. 16p.
Autor:
Chen, Huili1 (AUTHOR), Chun, Dain1 (AUTHOR), Lingineni, Karthik1,2 (AUTHOR), Guzy, Serge1,3 (AUTHOR), Cristofoletti, Rodrigo1 (AUTHOR), Hoechel, Joachim4 (AUTHOR), Jiao, Tianze5 (AUTHOR), Cicali, Brian1 (AUTHOR), Vozmediano, Valvanera1,6 (AUTHOR), Schmidt, Stephan1 (AUTHOR) sschmidt@cop.ufl.edu
Publikováno v:
CPT: Pharmacometrics & Systems Pharmacology. Nov2024, Vol. 13 Issue 11, p2016-2025. 10p.
Affect understanding capability is essential for social robots to autonomously interact with a group of users in an intuitive and reciprocal way. However, the challenge of multi-person affect understanding comes from not only the accurate perception
Externí odkaz:
http://arxiv.org/abs/2212.14128
Deep Neural Networks (DNNs) have been shown to be susceptible to Trojan attacks. Neural Trojan is a type of targeted poisoning attack that embeds the backdoor into the victim and is activated by the trigger in the input space. The increasing deployme
Externí odkaz:
http://arxiv.org/abs/2208.04943
Autor:
Chen, Huili, Ding, Jie, Tramel, Eric, Wu, Shuang, Sahu, Anit Kumar, Avestimehr, Salman, Zhang, Tao
In the context of personalized federated learning (FL), the critical challenge is to balance local model improvement and global model tuning when the personal and global objectives may not be exactly aligned. Inspired by Bayesian hierarchical models,
Externí odkaz:
http://arxiv.org/abs/2204.08069
This paper proposes AdaTest, a novel adaptive test pattern generation framework for efficient and reliable Hardware Trojan (HT) detection. HT is a backdoor attack that tampers with the design of victim integrated circuits (ICs). AdaTest improves the
Externí odkaz:
http://arxiv.org/abs/2204.06117
With the surge of Machine Learning (ML), An emerging amount of intelligent applications have been developed. Deep Neural Networks (DNNs) have demonstrated unprecedented performance across various fields such as medical diagnosis and autonomous drivin
Externí odkaz:
http://arxiv.org/abs/2204.04329