Show simple item record

dc.contributor.authorKong, Weiyi
dc.contributor.authorHu, Jing
dc.contributor.authorHuang, Wei
dc.contributor.authorLuo, Sang
dc.contributor.authorWen, Wu
dc.date.accessioned2026-08-20T21:27:35Z
dc.date.available2026-08-20T21:27:35Z
dc.date.copyright2026/03/24
dc.date.issued2026
dc.identifier.otherJCCEE5.CPENG-7122.pdf
dc.identifier.urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4314487
dc.description.abstractAbstractIn asphalt mixture research, deep learning networks have been widely applied to analyze slice images, serving as a foundation for numerous further valuable research. However, the effectiveness of these networks is hindered by the high cost of ...Practical ApplicationsThis study proposes a novel slice image translation network, SIT-GAN, for effective data augmentation of asphalt mixture slice image datasets. SIT-GAN enables high-quality bidirectional generation between various types of mixture ...
dc.publisherAmerican Society of Civil Engineers
dc.titleSIT-GAN: A Slice Image Translation Network for Asphalt Mixture
dc.typeJournal Article
dc.journal.volume40
dc.journal.issue4
dc.journal.titleJournal of Computing in Civil Engineering
dc.identifier.doi10.1061/JCCEE5.CPENG-7122
dc.journal.fristpage04026037-1
dc.journal.lastpage04026037-16
dc.page16
dc.treeJournal of Computing in Civil Engineering:;2026:;Volume ( 040 ):;issue: 004
dc.contenttypeFulltext


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record