Chinese Journal of Liquid Crystals and Displays, Volume. 40, Issue 5, 773(2025)
Improved autonomous driving object detection based on YOLOv8s
[1] HAN S M, XIAO F, CHENG W S. Overview of the application of deep reinforcement learning in autonomous driving systems[J]. Journal of Xihua University (Natural Science Edition), 42, 25-31(2023).
[3] REN S Q, HE K M, GIRSHICK R et al. Faster R-CNN: towards real-time object detection with region proposal networks[C], 91-99(2015).
[4] YANG F F, LI J. Research review of YOLO target detection algorithm for autopilot[J]. Automotive Engineer, 1-11(2023).
[7] XIE J, DENG Y M, WANG R M. Improved traffic sign detection algorithm based on YOLOv8s[J]. Computer Engineering, 50, 338-349(2024).
[14] TONG Z J, CHEN Y H, XU Z W et al. Wise-IoU: bounding box regression loss with dynamic focusing mechanism[J/OL]. arXiv, 2301-10051(2023).
[17] GEYER J, KASSAHUN Y, MAHMUDI M et al. A2D2: Audi autonomous driving dataset[J/OL]. arXiv, 2004-06320(2020).
[21] WANG C C, HE W, NIE Y et al. Gold-YOLO: efficient object detector via gather-and-distribute mechanism[C], 2224(2024).
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Longchun WANG, Wei FANG, Lijuan ZHANG, Dongming LI. Improved autonomous driving object detection based on YOLOv8s[J]. Chinese Journal of Liquid Crystals and Displays, 2025, 40(5): 773
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Received: Sep. 20, 2024
Accepted: --
Published Online: Jun. 18, 2025
The Author Email: Dongming LI (LDM0214@163.com)