This project develops a framework to assess the quality of multimodal perception in underwater surveillance. By integrating diverse sensors and machine learning models, it ensures accurate object detection and recognition in autonomous underwater vehicles. The approach enhances operatioNol reliability and effectiveness in complex aquatic environments.
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