Infrared and Laser Engineering, Volume. 52, Issue 8, 20230245(2023)
An infrared vehicle detection method based on improved YOLOv5
Figures & Tables(12)
Fig. 5. (a) FPN structure, adds an upward path from small-sized feature map; (b) PANet structure, adds a downward path from large-sized feature map based on FPN; (c) BiFPN structure; (d) Z-BiFPN
Fig. 7. (a) An example of a self-collected dataset; (b) An example of SCUT_FIR_Pedestrian_Dataset; (c) An example of MULTISPECTRAL DATASET
Fig. 10. Comparison of detection results. (a) Original image; (b) YOLOv5; (c) Improved YOLOv5
Table 1. Experimental results of different improvement methods
View tableView in ArticleTable 1. Experimental results of different improvement methods
a b c d e YOLOv5s √ √ √ √ √ CFG √ √ √ √ Four Head √ √ √ Z-BiFPN √ √ Decoupled Head √ AP-bus 88.5% 85.3% 87.1% 86.0% 89.4% AP-truck 81.0% 81.2% 82.9% 81.0% 85.4% AP-car 89.6% 88.7% 89.1% 89.6% 90.3% AP-van 78.3% 76.4% 77.8% 79.8% 82.6% AP-person 79.3% 82.6% 81.0% 79.7% 83.5% AP-bicycle 72.0% 76.6% 75.7% 79.5% 86.2% AP-elecmot 79.0% 80.1% 80.2% 82.5% 79.7% P 86.5% 89.4% 85.8% 86.9% 88.2% R 73.8% 75.4% 74.7% 76.7% 77.4% mAP 81.1 %81.6 %82.0 %82.6 %85.3 %
Table 2. Comparison of different object detection algorithms
View tableView in ArticleTable 2. Comparison of different object detection algorithms
Models SSD YOLOv3 YOLOv5 YOLOR-W6 YOLOv7-tiny YOLOX Ours AP-bus 76.4% 85.9% 88.5% 81.7% 85.7% 87.6% 89.4% AP-truck 88.0% 83.8% 81.0% 82.3% 82.4% 84.2% 85.4% AP-car 68.7% 83.3% 89.6% 90.1% 90.8% 90.3% 90.3% AP-van 63.2% 71.9% 78.3% 80.3% 79.2% 82.1% 82.6% AP-person 35.8% 70.1% 79.3% 76.9% 75.1% 81.5% 83.5% AP-bicycle 41.9% 50.2% 72.0% 44.7% 53.0% 78.3% 86.2% AP-elecmot 47.3% 65.6% 79.0% 80.5% 65.3% 80.7% 79.7% mAP 60.2% 73.0% 81.1% 76.6% 75.9% 83.5% 85.3% Parameters 24.4×106 61.6×106 7.0×106 79.3×106 6.0×106 8.9×106 10.4×106 Weight/MB 93.7 235.2 13.7 151.8 11.7 17.3 20.3
Tools
Get Citation
Copy Citation Text
Xuezhi Zhang, Hongdong Zhao, Weina Liu, Yiming Zhao, Song Guan. An infrared vehicle detection method based on improved YOLOv5[J]. Infrared and Laser Engineering, 2023, 52(8): 20230245
Paper Information
Category: Image processing
Received: Apr. 23, 2023
Accepted: --
Published Online: Oct. 19, 2023
The Author Email:
© Copyright 2018-2021 | Chinese Laser Press.
All Rights Reserved 沪ICP备15018463号-20