Mr. Yuchun Chu Profile

Yuchun Chu

at Ocean Univ of China

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Proceedings Article | 16 February 2022 Paper

Research on detection methods of high beam in night driving vehicles

Yuchun Chu, Hang Gong, Xue-fang Wang, Peishun Liu

Proceedings Volume 12083, 120832L (2022) https://doi.org/10.1117/12.2623207

KEYWORDS: Detection and tracking algorithms, Data modeling, Feature extraction, Target detection, Image enhancement, Performance modeling, Evolutionary algorithms, Convolution, Neural networks, Statistical analysis

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In order to solve the problem that it is difficult to control the abuse of high beam at night, a high beam detection algorithm YOLO-CAU based on YOLOv4 is designed and implemented. Then, aiming at the problem that it is difficult deployed on devices with limited computing power with a complex neural network, we apply the model compression algorithm of knowledge distillation to the image object detection task, and conducts distillation training on the YOLOCAU model with the high beam data set, transferring the knowledge learned by YOLO-CAU to a simple network (YOLO-CAU-S) with less computation and faster detection speed. Compared with the existing knowledge distillation algorithm, the algorithm designed in this paper not only restricts the output of the student network to be close to the output of the teacher, but also proposes a multi-scale pixel attention module to construct the attention feature maps of the teacher model and student model, which further transfers the strong attention of the teacher network to the student. The experimental results show that the knowledge distillation algorithm designed in this paper can greatly improve the detection efficiency of the model on the premise of ensuring the detection accuracy, and the compressed model parameters are only 6% of the teacher network.

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