EMA_Faster_C2f Schematic Diagram.

<div><p>Road damage detection is of great significance to traffic safety and road maintenance. However, the existing target detection technology still has shortcomings in accuracy, real-time and adaptability. In order to meet this challenge, this study constructed SEA-YOLO v8 model for r...

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Bibliographic Details
Main Author:	Yuxi Zhao (1797436) (author)
Other Authors:	Baoyong Shi (21568164) (author), Xiaoguang Duan (1554544) (author), Wenxing Zhu (14589422) (author), Liying Ren (11143129) (author), Chang Liao (564787) (author)
Published:	2025
Subjects:	Ecology Space Science Biological Sciences not elsewhere classified Information Systems not elsewhere classified utilize feature information rdd2022 dataset show improve feature representation feature fusion capability road damage detection road damage assessment detect road damage limited hardware resources yolo v8 model time target detection high detection accuracy study constructed sea material resources road maintenance yolov8 model traffic safety sustainable development selectively focus sbs module save manpower provide guidance neck component key areas great significance experimental results different layers computational complexity achieved 63 accurately locate
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EMA_Faster_C2f Schematic Diagram.

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