Underwater Object Tracking and Classification of Marine Animals

This research study focuses on the development and implementation of a comprehensive underwater object tracking and marine life classification system using the YOLO (You Only Look Once) architecture. The primary objective of this research study is to enhance the efficiency of underwater monitoring and exploration by employing computer vision techniques. The paper involves the detection of submerged objects and the subsequent classification of marine life, contributing to advancements in aquatic research and environmental monitoring. Also, this study aims to find the best solution for underwater challenges by exploring and comparing different algorithms.