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contributor authorYao, Hui
contributor authorYu, Yifan
contributor authorZhang, Huiting
contributor authorLiu, Yanhao
contributor authorWang, Min
date accessioned2026-08-20T12:02:09Z
date available2026-08-20T12:02:09Z
date copyright2025/12/13
date issued2026
identifier otherJPEODX.PVENG-1869.pdf
identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4313004
description abstractAbstractEdge computing technology enables in situ diagnosis based on neural networks in ground-penetrating radar (GPR) detection. However, there is a contradiction between the limited resources of radar terminal and the high resource demands of the ...This figure illustrates the architecture of a lightweight pavement defect detection algorithm based on Ground Penetrating Radar (GPR). The workflow begins with the input of a GPR image dataset, which is processed using an EfficientNet-YOLOv5 lightweight ...
publisherAmerican Society of Civil Engineers
titleA Lightweight Detection Algorithm for Pavement Structure Distress Based on Ground-Penetrating Radar Investigation and Joint Pruning
typeJournal Article
journal volume152
journal issue1
journal titleJournal of Transportation Engineering, Part B: Pavements
identifier doi10.1061/JPEODX.PVENG-1869
journal fristpage04025063-1
journal lastpage04025063-10
page10
treeJournal of Transportation Engineering, Part B: Pavements:;2026:;Volume ( 152 ):;issue: 001
contenttypeFulltext


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