Unstructured Road Defect Detection Algorithm Based on Semi-Supervised Learning

Detecting defects on unstructured roads is important for road traffic safety; however, annotated datasets required for detection is limited. This study proposes the Multi-Augmentation with Memory (MAM) semi-supervised object detection algorithm to address the lack of annotated datasets for unstructu...

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Bibliografiske detaljer

Hovedforfatter:	ZHU Siyuan, LI Jiasheng, ZOU Danping, HE Di, YU Wenxian
Format:	Artigo
Sprog:	Inglês
Udgivet:	Editorial Office of Computer Engineering 2025-09-01
Serier:	Jisuanji gongcheng
Fag:	unstructured road|defect object detection|semi-supervised learning|pseudo label|cache mechanism|hybrid data augmentation
Online adgang:	https://www.ecice06.com/fileup/1000-3428/PDF/jsjgc-51-9-14.pdf
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