Journal of Applied Optics, Volume. 44, Issue 5, 1054(2023)

Infrared ship target detection algorithm based on improved YOLOX-S

Shuli LOU1, Yan WANG1、*, Jianqin GUO2, and Weifeng GONG3
Author Affiliations
  • 1School of Physics and Electronic Information, Yantai University, Yantai 264005, China
  • 2Department of Electronics and Communication Engineering, Shandong College of Electronic Technology, Jinan 250200, China
  • 3State Key Laboratory of High-end Server and Storage Technology, Jinan 250101, China
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    Infrared ship target detection and recognition technology is the key technology of infrared imaging guidance for anti-ship missile, which is of great significance to the guidance performance of weapon equipment. For the accuracy and speed in complex environment, an infrared ship target detection algorithm based on YOLOX-S was proposed. Firstly, the depthwise separable convolution (DSC) was introduced to replace the traditional convolution in the feature pyramid network (FPN) and YOLOHead residual structures, which could reduce the amount of parameters of the model. Secondly, the ECANet channel attention mechanism was introduced to improve the attention of network, which could reduce the false detection rate and missed detection rate of ship targets. Finally, the CIoU loss function was used to further improve the detection accuracy of the network. The experimental results show that the average precision (AP) of the optimized algorithm reaches 98% and the detection speed is 56 frame/s. Compared with the previous YOLOX-S algorithm, the detection speed and the average precision are improved by 6 frame/s and 3%, respectively, and the model is more lightweight. The experimental results fully prove that the proposed algorithm can effectively complete the infrared ship target detection task.

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    Shuli LOU, Yan WANG, Jianqin GUO, Weifeng GONG. Infrared ship target detection algorithm based on improved YOLOX-S[J]. Journal of Applied Optics, 2023, 44(5): 1054

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    Paper Information

    Category: Research Articles

    Received: Sep. 21, 2022

    Accepted: --

    Published Online: Mar. 12, 2024

    The Author Email: WANG Yan (王岩)

    DOI:10.5768/JAO202344.0502006

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