Deep Learning–Based Quantitative Evaluation of the Relationship between Damage Evolution and Seismic Capacity of RC Columns

dc.contributor.author	Wen, Yue
dc.contributor.author	Yuan, Dan
dc.contributor.author	Cai, Gaochuang
dc.date.accessioned	2026-08-20T21:23:53Z
dc.date.available	2026-08-20T21:23:53Z
dc.date.copyright	2025/07/28
dc.date.issued	2025
dc.identifier.other	JCCEE5.CPENG-6476.pdf
dc.identifier.uri	http://yetl.yabesh.ir/yetl1/handle/yetl/4314387
dc.description.abstract	AbstractGiven the rapid advancement of AI technology, deep learning (DL) is increasingly being utilized to assess the damage of reinforced concrete (RC) elements. This paper adopts DL to discuss the relationship between the surface damage and the seismic ...
dc.publisher	American Society of Civil Engineers
dc.title	Deep Learning–Based Quantitative Evaluation of the Relationship between Damage Evolution and Seismic Capacity of RC Columns
dc.type	Journal Article
dc.journal.volume	39
dc.journal.issue	6
dc.journal.title	Journal of Computing in Civil Engineering
dc.identifier.doi	10.1061/JCCEE5.CPENG-6476
dc.journal.fristpage	04025087-1
dc.journal.lastpage	04025087-15
dc.page	15
dc.tree	Journal of Computing in Civil Engineering:;2025:;Volume ( 039 ):;issue: 006
dc.contenttype	Fulltext