Journal of Advances in Artificial Life Robotics
Online ISSN : 2435-8061
ISSN-L : 2435-8061
A lightweight pedestrian vehicle detection algorithm based on YOLOV5
Zhihui ChenXiaoyan ChenXiaoning YanShuangwu Zheng
著者情報
キーワード: pedestrian, vehicle, detection, YOLOv5
ジャーナル オープンアクセス

2022 年 2 巻 4 号 p. 171-176

詳細
抄録
With the continuous improvement of social development level, traffic has become complicated. Therefore, the detection of pedestrian and vehicles becomes important. There are many application scenarios for pedestrian-vehicle detection, such as autonomous driving and transportation. This paper mainly introduces the research status of pedestrian-vehicle detection, analyzes the advantages and disadvantages of various current target detection algorithms, and focuses on YOLOv5 algorithm. Because the YOLOv5 model is much smaller than YOLOv4, and YOLOv5 also has strong detection ability. Finally, YOLOv5 is used to carry out pedestrian-vehicle detection experiments. The results the detection accuracy is improved slightly.
著者関連情報
© 2022 ALife Robotics Corporation Ltd.

この記事はクリエイティブ・コモンズ [表示 - 非営利 4.0 国際]ライセンスの下に提供されています。
https://creativecommons.org/licenses/by-nc/4.0/deed.ja
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