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contributor authorKong, Weiyi
contributor authorHu, Jing
contributor authorHuang, Wei
contributor authorLuo, Sang
contributor authorWen, Wu
date accessioned2026-08-20T21:27:35Z
date available2026-08-20T21:27:35Z
date copyright2026/03/24
date issued2026
identifier otherJCCEE5.CPENG-7122.pdf
identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4314487
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 ...
publisherAmerican Society of Civil Engineers
titleSIT-GAN: A Slice Image Translation Network for Asphalt Mixture
typeJournal Article
journal volume40
journal issue4
journal titleJournal of Computing in Civil Engineering
identifier doi10.1061/JCCEE5.CPENG-7122
journal fristpage04026037-1
journal lastpage04026037-16
page16
treeJournal of Computing in Civil Engineering:;2026:;Volume ( 040 ):;issue: 004
contenttypeFulltext


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