Zobrazeno 1 - 10
of 47
pro vyhledávání: '"Zhang Hanrong"'
Knowledge graph (KG) technology is extensively utilized in many areas, and many companies offer applications based on KG. Nonetheless, the majority of KG platforms necessitate expertise and tremendous time and effort of users to construct KG records
Externí odkaz:
http://arxiv.org/abs/2410.08094
Autor:
Zhang, Hanrong, Huang, Jingyuan, Mei, Kai, Yao, Yifei, Wang, Zhenting, Zhan, Chenlu, Wang, Hongwei, Zhang, Yongfeng
Although LLM-based agents, powered by Large Language Models (LLMs), can use external tools and memory mechanisms to solve complex real-world tasks, they may also introduce critical security vulnerabilities. However, the existing literature does not c
Externí odkaz:
http://arxiv.org/abs/2410.02644
Autor:
Yao, Yifei, Zhang, Hanrong
In real-world clinical settings, data distributions evolve over time, with a continuous influx of new, limited disease cases. Therefore, class incremental learning is of great significance, i.e., deep learning models are required to learn new class k
Externí odkaz:
http://arxiv.org/abs/2409.07757
Autor:
Zhang, Hanrong, Wang, Zhenting, Han, Tingxu, Jin, Mingyu, Zhan, Chenlu, Du, Mengnan, Wang, Hongwei, Ma, Shiqing
Self-supervised learning models are vulnerable to backdoor attacks. Existing backdoor attacks that are effective in self-supervised learning often involve noticeable triggers, like colored patches, which are vulnerable to human inspection. In this pa
Externí odkaz:
http://arxiv.org/abs/2405.14672
Autor:
Wang, Xingyue, Zhang, Hanrong, Qiao, Xinlong, Ma, Ke, Tao, Shuting, Peng, Peng, Wang, Hongwei
Fault diagnosis is crucial in monitoring machines within industrial processes. With the increasing complexity of working conditions and demand for safety during production, diverse diagnosis methods are required, and an integrated fault diagnosis sys
Externí odkaz:
http://arxiv.org/abs/2306.15266
Publikováno v:
Natural Gas Industry B, Vol 1, Iss 2, Pp 185-191 (2014)
Burial depth, thickness, total organic carbon (TOC) content, brittleness and fracture development of shale reservoirs are the main geologic indexes in the evaluation of sweet spots in shale gas plays. Taking the 2nd interval of Da'anzhai shale of the
Externí odkaz:
https://doaj.org/article/935e695744b44b9a809bfcba10764b23
Intelligent fault diagnosis has made extraordinary advancements currently. Nonetheless, few works tackle class-incremental learning for fault diagnosis under limited fault data, i.e., imbalanced and long-tailed fault diagnosis, which brings about var
Externí odkaz:
http://arxiv.org/abs/2302.05929
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.
Autor:
Hu, Dongfeng, Wang, Liangjun, Zhang, Hanrong, Duan, Jinbao, Xia, Wenqian, Liu, Zhujiang, Wei, Quanchao, Wang, Kun, Pan, Lei
Publikováno v:
In Natural Gas Industry B February 2021 8(1):13-23
Autor:
Chen, Junxin, Zeng, Chuimian, Jin, Jiewen, Zhang, Pengyuan, Zhang, Yilin, Zhang, Hanrong, Li, Yanbing, Guan, Hongyu
Publikováno v:
Endocrine (1355008X); Jul2024, Vol. 85 Issue 1, p238-249, 12p