Road target detection under complex weather based on YOLOv5-CGα algorithm

Menghao Li; Miao Liu

doi:10.1117/12.3017310

15 December 2023 Road target detection under complex weather based on YOLOv5-CGα algorithm

Menghao Li, Miao Liu

Proceedings Volume 12971, Third International Conference on Optics and Communication Technology (ICOCT 2023); 129710I (2023) https://doi.org/10.1117/12.3017310
Event: Third International Conference on Optics and Communication Technology (ICOCT 2023), 2023, Changchun, China

Abstract

Accuracy of the detection algorithm is very important for the safety of autonomous driving in complex road target detection and recognition. Therefore, this study proposes a novel lightweight YOLOv5-CGα target identification algorithm that focuses on optimizing the algorithm's lightness and accuracy. First, the algorithm adds the CBAM (Convolutional Block Attention Module) to improve the network's capacity to extract target characteristics and detection accuracy; secondly, by replacing the ordinary convolution module with the Ghost Bottleneck module in order to compress the parameters of the network and reduce the overall amount of model computation; finally, the original C-IoU (Complete-Intersection Over Union) model's loss function is changed by the α-IoU (α-Intersection Over Union) loss function, leading the model training process to converge faster. The mAP of the YOLOv5-CGα algorithm for the detection of road targets can reach 97.4%, according to experimental results on the BDD100K dataset. The simulation results show that compared with the performance of YOLOv3 and YOLOv5 algorithms, the YOLOv5-CGα algorithm improves the mAP of detecting road targets by 2.7% and by 1.4%. This algorithm only needs half of the parameters in order to enhance on-road target recognition accuracy, which may balance the algorithm's small weight with the issue of accurate road target detection.

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Menghao Li and Miao Liu "Road target detection under complex weather based on YOLOv5-CGα algorithm", Proc. SPIE 12971, Third International Conference on Optics and Communication Technology (ICOCT 2023), 129710I (15 December 2023); https://doi.org/10.1117/12.3017310

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KEYWORDS

Target detection

Detection and tracking algorithms

Roads

Education and training

Evolutionary algorithms

Object detection

Performance modeling

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