To improve the intelligence level of signal lamp detection,an intelligent signal lamp detection method based on YOLOv8 algorithm is proposed,which can randomly divide the self built signal lamp dataset into a training set and a validation set in a 4:1 ratio,and train a deep learning model after preprocessing.The results show that the model can converge and achieve end-to-end detection of signal lamp position and color,which has good potential for signal lamp detection tasks.
关键词
信号灯检测/YOLOv8/深度学习/平均精度均值(mAP)/智能化轨道交通
Key words
signal lamp detection/YOLOv8/deep learning/mean average precision(mAP)/intelligent rail transport
维普
万方数据