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An improved YOLOv3-tiny algorithm for vehicle detection in natural scenes 被引量:2
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作者 Bingqiang Huang Haiping Lin +2 位作者 Zejun Hu Xinjian Xiang jiana yao 《IET Cyber-Systems and Robotics》 EI 2021年第3期256-264,共9页
YOLO(You Only Look Once),as a target detection algorithm with good speed and precision,is widely used in the industry.In the process of driving,the vehicle image captured by the driving camera is detected and it extra... YOLO(You Only Look Once),as a target detection algorithm with good speed and precision,is widely used in the industry.In the process of driving,the vehicle image captured by the driving camera is detected and it extracts the license plate and the front part of the vehicle.Compared with the network structure of YOLOv3-tiny algorithm,the acquisition method of anchor box is improved by combining the Birch algorithm.In order to improve the real-time performance,the original two-scale detection is added to the multi-scale prediction of three-scale detection to ensure its accuracy.Finally,the experimental results show that the improved YOLOv3-tiny network structure proposed in this study can improve the performance of mean-average-precision,intersection over union and speed by 5.99%,17.52%and 48.4%,respectively,and the algorithm has certain robustness. 展开更多
关键词 ALGORITHM driving NETWORK
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