Human-vehicle detection based on YOLOv5

DOI

Description

With the continuous improvement of social development level, traffic has become complicated. Therefore, the detection of people and vehicles becomes important. There are many application scenarios for human-vehicle detection, such as autonomous driving and transportation. This paper mainly introduces the research status of humanvehicle 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 human-vehicle detection experiments. The results the detection accuracy is improved slightly.

Journal

Keywords

Details 詳細情報について

  • CRID
    1390573242527581952
  • DOI
    10.5954/icarob.2022.os11-1
  • ISSN
    21887829
  • Text Lang
    en
  • Data Source
    • JaLC
    • Crossref
  • Abstract License Flag
    Disallowed

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