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.
signal lamp detectionYOLOv8deep learningmean average precision(mAP)intelligent rail transport
维普
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