Improving the SAR image ship target detection model of YOLOv8

doi:10.13474/j.cnki.11-2246.2024.1204

Abstract

Abstract: In the SAR image ship target detection task, due to factors such as complex coastal background and multi-scale ship targets, ship targets may have low detection accuracy and missed detections during the detection process. In response to the above issues, this article proposes an improved SAR image ship target detection model based on YOLOv8s, and conducts experimental verification by SSDD and HRSID datasets, with better performance than other classical algorithms.

Key words: ship target detection, SAR imaging, residual enhancement, deformable convolution, dynamic sparse attention

CLC Number:

P237

YANG Mingqiu, CHEN Guokun, ZUO Xiaoqing, DONG Yan. Improving the SAR image ship target detection model of YOLOv8[J]. Bulletin of Surveying and Mapping, 2024, 0(12): 18-23.

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