YOLOv5模型的火车车厢目标识别技术研究

Research on Train Carriage Target Recognition Technology Based on YOLOv5 Model

在火车运行过程中,可通过智能化程序完成车厢目标识别,准确定位车厢位置,避免出现差错,保证火车正常运行。本研究主要探讨基于YOLOv5模型的应用原理与特点,分析YOLOv5模型在火车车厢目标识别技术的应用要点,完成深度学习与数据集训练,借助数据集识别火车车厢目标。经过研究,以YOLOv5模型的火车车厢目标识别系统识别准确率在99%以上,满足火车运行中的车厢识别需求,为类似识别系统研究提供参考。

During train operation,intelligent programs can be used to achieve carriage target recognition,accurately locate carriage positions,avoid errors,and ensure normal train operation.This study mainly explores the application principles and characteristics of the YOLOv5 model,analyzes the application points of the YOLOv5 model in train carriage target recognition technology,completes deep learning and dataset training,and uses the dataset to identify train carriage targets.After research,the recognition accuracy of the YOLOv5 model based train carriage target recognition system is over 99%,which meets the needs of carriage recognition during train operation and provides reference for similar recognition system research.