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Indoor Parking Space Detection Based on Improved YOLOv5m
更新时间：2024-05-16
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    • Indoor Parking Space Detection Based on Improved YOLOv5m

    • “研究团队针对室内停车场景下目标停车位检测难题，提出创新算法。该算法在YOLOv5m基础上增加小目标检测层，并引入坐标注意力机制，有效减少冗余信息，提升检测精度。同时，团队建立包含8100张图像的地下车位标注数据集进行实验。该算法平均检测精度达98.214%，准确率和召回率均超96%。这一成果显著提高了模型精度和实时性，为室内停车场景下的停车位检测提供了可行方案。”
      ”
    • Software Guide   Vol. 23, Issue 4, Pages: 157-163(2024)

    • DOI：10.11907/rjdk.231405    

      CLC： TP391.41

    • Published：15 April 2024，

      Received：20 April 2023，

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  • LI Yue,MA Shidian,HUANG Yuxuan.Indoor Parking Space Detection Based on Improved YOLOv5m[J].Software Guide,2024,23(04):157-163. DOI： 10.11907/rjdk.231405.

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