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A MSA-YOLO Obstacle Detection Algorithm for Rail Transit in Foggy Weather

Obstacles on rail transit significantly compromise operational safety, particularly under dense fog conditions. To address missed and false detections in traditional rail transit detection methods, this paper proposes a multi-scale adaptive YOLO (MSA-YOLO) algorithm. The algorithm incorporates six f...

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Principais autores: Jian Chen, Donghui Li, Weiqiang Qu, Zhiwei Wang
Format: Artigo
Sprog:Inglês
Udgivet: MDPI AG 2024-08-01
Serier:Applied Sciences
Fag:
multi-scale adaptive YOLO
obstacle detection
rail transit
foggy weather
deep learning
Online adgang:https://www.mdpi.com/2076-3417/14/16/7322
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