Improved autonomous driving object detection based on YOLOv8s
Image Processing|更新时间:2025-05-13
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Improved autonomous driving object detection based on YOLOv8s
“In the field of autonomous driving, researchers have proposed an improved object detection algorithm based on YOLOv8s, which improves detection accuracy and model efficiency by optimizing network structure and loss function.”
Chinese Journal of Liquid Crystals and DisplaysVol. 40, Issue 5, Pages: 773-784(2025)
作者机构:
1.南京信息工程大学 计算机学院, 江苏 南京 210044
2.无锡学院 物联网工程学院, 江苏 无锡 214105
作者简介:
基金信息:
National Natural Science Foundation of China project(61801439);Jilin Provincial Science and Technology Development Plan(20210204050YY);Scientific Research Project of Jilin Provincial Department of Ecological Environment(吉环科字第2021-07号);Wuxi University Research Start-up Fund for Introduced Talents(2023r004;2023r006)
WANG Longchun, FANG Wei, ZHANG Lijuan, et al. Improved autonomous driving object detection based on YOLOv8s[J]. Chinese journal of liquid crystals and displays, 2025, 40(5): 773-784.
DOI:
WANG Longchun, FANG Wei, ZHANG Lijuan, et al. Improved autonomous driving object detection based on YOLOv8s[J]. Chinese journal of liquid crystals and displays, 2025, 40(5): 773-784. DOI: 10.37188/CJLCD.2024-0290. CSTR: 32172.14.CJLCD.2024-0290.
Improved autonomous driving object detection based on YOLOv8s