Multidimensional Feature Collaborative Fusion Pyramid for Ship Wake Detection

With the rapid development of the marine resource development and maritime transportation industries, there has been a sharp increase in the number of ships sailing on the sea surface, leading to frequent maritime traffic accidents and illegal incidents. These events not only threaten maritime traffic safety but also cause serious damage to the marine ecological environment. This study proposes an improved detection method for ship wake targets in satellite remote sensing images based on the wake characteristics. The method utilizes Multidimensional Feature Collaborative Fusion Pyramid(MCFP) and Multidimensional Balance DepthWise Attention(MBDA) to enhance detection accuracy and efficiency. Experiments using the SWIM dataset demonstrate the proposed method’s significant advantage in detection accuracy over existing techniques.