Improved site truck gate detection algorithm based on deep learning

Chang Liu; Yutong Cui; Taizhou Yang; Guopeng Zhang; Wei Ren; Dawei Jiang; Wei Chen

doi:10.1117/12.2651112

14 October 2022 Improved site truck gate detection algorithm based on deep learning

Chang Liu, Yutong Cui, Taizhou Yang, Guopeng Zhang, Wei Ren, Dawei Jiang, Wei Chen

Proceedings Volume 12343, 2nd International Conference on Laser, Optics and Optoelectronic Technology (LOPET 2022); 123432M (2022) https://doi.org/10.1117/12.2651112
Event: 2nd International Conference on Laser, Optics and Optoelectronic Technology (LOPET 2022), 2022, Qingdao, China

Abstract

At present, with the rapid development of industrialization, construction and real estate industries have also been developed, but the verification and entrance control of vehicles carrying large equipment and cement also need to be checked manually, causing a lot of artificial burden. In this paper, an improved algorithm based on deep learning is proposed to realize unmanned gate detection. The distance between the vehicle and the gate can be judged by real-time detection of whether there is a vehicle passing by, so as to make the instruction of lifting the gate or lowering the gate. Compared with the traditional gate detection, the use of a lower cost of ordinary cameras can be completed, so as to save a lot of cost, and can detect the vehicle information in real time, consistent with China's industrial intelligence strategy. In this paper, YoLoV4 algorithm is used and mobilnet-V3 algorithm is used to replace the original main network structure, which greatly reduces the number of parameters of the algorithm structure and improves the running speed of the algorithm, so that it can reach the real-time state. VOC data sets were used for training and detection, and the experiment proved that the speed was greatly improved and real-time vehicle detection could be realized.

Citation Download Citation

Chang Liu, Yutong Cui, Taizhou Yang, Guopeng Zhang, Wei Ren, Dawei Jiang, and Wei Chen "Improved site truck gate detection algorithm based on deep learning", Proc. SPIE 12343, 2nd International Conference on Laser, Optics and Optoelectronic Technology (LOPET 2022), 123432M (14 October 2022); https://doi.org/10.1117/12.2651112

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KEYWORDS

Convolution

Detection and tracking algorithms

Evolutionary algorithms

Feature extraction

Target detection

Neural networks

Computer vision technology

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