A Lightweight and High-Precision Target Detection Algorithm for Unmanned Surface Vehicles

Unmanned Surface Vehicles (USVs) play a crucial role in maritime operations, demanding accurate and efficient target detection. However, existing detection algorithms often struggle with balancing high precision and lightweight computation, which is critical for real-time deployment on resource-constrained platforms. This paper proposes a novel lightweight and high-precision target detection algorithm tailored for USVs. By integrating an optimized backbone network with an improved feature fusion strategy, our approach significantly enhances detection accuracy while maintaining a low computational burden. Experimental results on benchmark datasets demonstrate that our method outperforms conventional models in terms of both precision and efficiency, making it well-suited for real-world maritime applications.