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基于改进YOLOv8模型的铁路沿线彩钢瓦隐患识别方法

Method for identifying hidden dangers of color steel tiles along railway lines based on improved YOLOv8 model

  • 摘要: 鉴于铁路轨道周边彩钢瓦隐患的人工巡检效率低且周期长,文章基于改进YOLOv8模型,设计了铁路沿线彩钢瓦隐患识别方法。对YOLOv8模型进行改进,在YOLOv8模型中添加一个区域损失函数,提升小尺寸彩钢瓦的识别精度。在自行构建的彩钢瓦专用数据集上进行实验验证,结果显示,相较于未改进的YOLOv8模型,基于改进YOLOv8模型的铁路沿线彩钢瓦隐患识别方法在识别性能上有较为显著的提升,能够高效而精确地检测铁路沿线的彩钢瓦隐患,为铁路安全运营提供技术支持。

     

    Abstract: Regarding the low efficiency and long cycle of manual inspection of hidden dangers in color steel tiles around railway tracks, this paper designed a method for identifying hidden dangers in color steel tiles along railway lines based on an improved YOLOv8 model. The paper improved the YOLOv8 model by adding Area Loss function to enhance the identifying accuracy, conducted experimental verification on a self-developed dataset for color steel tiles. The results showed that compared with the unimproved YOLOv8 model, the method for identifying hidden dangers in color steel tiles along railway lines based on the improved YOLOv8 model had significant improvement in identifying performance. This method can efficiently and accurately detect hidden dangers in color steel tiles along railway lines, provides technical support for railway safety operation.

     

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