YOLO-R:road damage detector based on dynamic receptive fields and lightweight design

To address the challenges of missed detection, false detection, and low efficiency in road damage detection, this paper proposes an enhanced road damage detection model YOLO-R based on improved YOLOv8. First, we construct a collaborative module combining Switchable Atrous Convolution (SAC) with C2f....

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Bibliographic Details
Published in:	Signal, image and video processing Vol. 19; no. 11; p. 885
Main Authors:	Mao, Jinghong, Wang, Mei, Liu, Zhenghong
Format:	Journal Article
Language:	English
Published:	Heidelberg Springer Nature B.V 01.11.2025
Subjects:	Accuracy Algorithms Boxes Complexity Computing costs Convolution Cracks Damage detection Deep learning Efficiency Feature extraction Modules Object recognition Real time Roads & highways China
ISSN:	1863-1703, 1863-1711
Online Access:	Get full text
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