Multi-source ship image fusion detection method based on MFFDet-R

A multi-source ship image fusion detection method based on multi-modal feature fusion detection network based on rotation (MFFDet-R) is proposed to address the issue of ship target fusion detection for multi-source images obtained by unmanned aerial vehicles. Firstly, a single-stage anchor free frame design is adopted to reduce computational complexity to improve detection speed. Subsequently, rotation task alignment learning is adopted for label allocation and alignment to improve detection accuracy. Then, a multimodal feature fusion network is designed to achieve full fusion of multimodal features. Finally, detection heads and angle prediction heads are designed for specific scenarios to improve network detection performance. Through experimental comparison and verification, the results show that the proposed method can effectively achieve fusion detection of multi-source ships, and its detection performance for ship targets in different scenarios is superior to other methods. © 2025 Chinese Institute of Electronics. All rights reserved.