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Deep learning-enhanced environment perception for autonomous driving: MDNet with CSP-DarkNet53

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成果类型:
期刊论文
作者:
Guo, Xuyao;Jiang, Feng;Chen, Quanzhen;Wang, Yuxuan;Sha, Kaiyue;...
通讯作者:
Jiang, F
作者机构:
[Jiang, Feng; Guo, Xuyao; Wang, Yuxuan; Jiang, F; Chen, Quanzhen; Sha, Kaiyue; Chen, Jing] Cent South Univ Forestry & Technol, Changsha, Peoples R China.
通讯机构:
[Jiang, F ] C
Cent South Univ Forestry & Technol, Changsha, Peoples R China.
语种:
英文
关键词:
Multitasking;driverless;Environment awareness;Traffic target and lane line detection
期刊:
PATTERN RECOGNITION
ISSN:
0031-3203
年:
2025
卷:
160
基金类别:
Natural Science Foundation of Hunan Province [2021JJ31142]; Sci-entific Innovation Fund for Post-graduates of Central South University of Forestry and Technology [2023CX02095]; Graduate Student Research and Innovation Programme Fund of Hunan Province [CX20230771]
机构署名:
本校为第一且通讯机构
摘要:
Implementing environmental perception in intelligent vehicles is a crucial application, but the parallel processing of numerous algorithms on the vehicle side is complex, and their integration remains a critical challenge. To address this problem, this paper proposes a multitask detection algorithm Multitask Detection Network (MDNet) based on Cross Stage Partial Networks with Darknet53 Backbone (CSP-DarkNet53) with high feature extraction capability, which can simultaneously detect vehicles, pedestrians, traffic lights, traffic signs, and bicycles as well as lane lines. MDNet obtains exception...

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