An Improved UNet Algorithm Based on Multiscale Features and Attention Modules for Underwater Salient Multi-Target Detection

Abstract

This paper improves UNet for underwater salient multi-target detection by combining multiscale feature extraction and attention modules. The method targets the difficult visual conditions common in underwater scenes, where object scale variation, turbidity, and background interference make reliable salient object detection challenging.

Shaojian Yang

Assistant Research Fellow / Postdoctoral Fellow

My research interests include underwater communications, distributed acoustic sensing and ocean Internet of Things.