基于改装电动车的中小目标检测
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科技厅重点研发计划(2020YFS0307)


Small and Medium-sized Object Detection Based on Modified Electric Vehicles
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    摘要:

    由于电动车的普及, 越来越多的电动车进行非法改装雨棚. 然而, 这种改装行为会增加一些安全隐患. 首先, 挡雨板会遮挡骑行者视野, 增加事故的风险. 其次当速度过快时, 挡雨板也会在不经意间擦伤行人, 带来极大地安全隐患, 给交通安全带来了严重威胁. 本文提出了一种改进的YOLOv7-tiny算法, 用于电动车非法改装检测. 首先在网络的结构上加入BiFormer注意力机制, 不仅可以捕获更多电动车细节的信息, 而且可以使得模型更加关注一些较小的目标信息. 其次将改进的特征金字塔结构和特征融合网络的张量拼接操作进行结合, 提升对中小型目标的检测能力. 最后对框架的ELAN模块和SPPCSPC模块进行改进和优化, 可以在不增加过多参数量的同时, 提升对中小目标的检测精度, 增强提取特征的效果.

    Abstract:

    Due to the popularity of electric vehicles, more and more electric vehicles are illegally modified with rain shields. However, this modification increases safety hazards. Firstly, rain shields block riders’ view, increasing the risk of accidents. Secondly, rain shields can inadvertently scratch pedestrians when the modified vehicles are at excessive speeds, posing a great safety hazard and a serious threat to traffic safety. This study proposes an improved YOLOv7-tiny algorithm for detecting illegally modified electric vehicles. Firstly, a BiFormer attention mechanism is added to the network structure, enabling the model to capture more details of electric vehicles and focus more on smaller target information. Secondly, an improved feature pyramid structure is combined with the tensor concatenation of a feature fusion network to enhance the detection ability of the model for small and medium-sized targets. Finally, the ELAN and SPPCSPC modules of the framework are optimized, which improves the detection accuracy of small and medium-sized targets and enhances the effectiveness of feature extraction without adding too many parameters.

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黄峻,刘涌.基于改装电动车的中小目标检测.计算机系统应用,,():1-8

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  • 收稿日期:2024-01-26
  • 最后修改日期:2024-02-29
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  • 在线发布日期: 2024-10-31
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