Jumi Park

Robust Maritime Object Detection under Adverse Conditions via Joint Semantic Learning without Extra Computational Overhead

This study addresses the challenge of robust object detection in maritime environments, where dynamic conditions such as fog, brightness variations, and motion blur can degrade accuracy. We propose a novel framework, Joint Semantic Learning (JSL), which combines ocean scene segmentation and object d