电子科技2025，Vol.38Issue(6)：23-29,7.DOI:10.16180/j.cnki.issn1007-7820.2025.06.004
基于深度学习的车位检测方法
A Parking Space Detection Method Based on Deep Learning
摘要
Abstract
In view of the problems such as single task and occlusion of key points in parking detection algorithm in automatic parking system,a YOLO(You Only Look Once)-based parking detection model is proposed by combining target detection and key point detection,which can simultaneously detect parking area,parking use and key points.The key point regression branch of parking space is added to the output end of YOLOv7-tiny(You Only Look Once version7-tiny)model and its coding design is carried out to improve the accuracy of model identification and positio-ning by improving the loss function.The attention mechanism is integrated in the backbone network to improve the fea-ture extraction capability of the network.The experimental results show that compared with YOLOv7-tiny,the average parking area recognition accuracy of the proposed model is increased by 1.8 percentage,and the parking space usage judgment accuracy is increased by 1.1 percentage.Moreover,the key point location function is added,and the success rate of location reaches 94.1％,indicating that the proposed method has high application value.关键词
自动泊车/遮挡/目标检测/YOLOv7-tiny/关键点检测/特征提取/注意力机制/损失函数Key words
automatic parking/occlusion/target detection/YOLOv7-tiny/keypoints detection/feature extraction/attention mechanism/loss function分类
计算机与自动化引用本文复制引用
唐玉良,张轩雄..基于深度学习的车位检测方法[J].电子科技,2025,38(6):23-29,7.基金项目
国家自然科学基金(62276167)National Natural Science Foundation of China(62276167) （62276167）
