Detection of ship targets in remote sensing image based on improved YOLOv5

XiaoJie Li; Lei Chen; DaYu Wang; HongWei Yang

doi:10.1117/12.2668063

20 April 2023 Detection of ship targets in remote sensing image based on improved YOLOv5

XiaoJie Li, Lei Chen, DaYu Wang, HongWei Yang

Proceedings Volume 12602, International Conference on Electronic Information Engineering and Computer Science (EIECS 2022); 1260216 (2023) https://doi.org/10.1117/12.2668063
Event: International Conference on Electronic Information Engineering and Computer Science (EIECS 2022), 2022, Changchun, China

Abstract

In view of the problems of ship target detection in remote sensing images, such as small ship targets, densely arranged ships, and arbitrary target directions, this paper proposes a target detection method based on improved YOLOv5. This method combines the improved DesnesNet and X-RFB modules to enhance the feature extraction of large-scale changing targets; it adds direction information on the basis of the traditional bounding box, and uses KFIOU instead of GIOU to perform curve optimization on the loss function; At the same time of quantification, high-speed and high-precision coexistence of ship target detection can be achieved. The experimental results show that: compared with the original YOLOv5 method, the map index of this method is improved from the original 91.0% to 96.5%, which is obviously better than the comparison method.

Citation Download Citation

XiaoJie Li, Lei Chen, DaYu Wang, and HongWei Yang "Detection of ship targets in remote sensing image based on improved YOLOv5", Proc. SPIE 12602, International Conference on Electronic Information Engineering and Computer Science (EIECS 2022), 1260216 (20 April 2023); https://doi.org/10.1117/12.2668063

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