Research on Small Target Ship Recognition based on Feature Fusion and Hybrid Attention

Abstract: Objective The aim is to address the issue of low recognition rate in network models due to the insignificance of features in small target ships. Methods A fusion method based on the integration of image and motion features is proposed to enrich the feature representation of small ships in scenarios where the features of small target ship images are not prominent. Additionally, hybrid attention model can incorporates prior information of ship targets under data-driven conditions to enhance the model's perception and utilization of key features. Effects The proposed method achieves the recognition of small target ships with a resolution of 720P at a distance of up to 4 kilometers, enabling wide-area ship recognition and localization functionality. Conclusion The improved target recognition network exhibits pixel-level ship detection capability while also demonstrating robustness against environmental noise interference. It overcomes the bottleneck of low recognition rate in small target ship detection by network models..