Challenges and Insights in Underwater Fish Detection Using YOLO-Fish Models
Abstract:
This study evaluates the performance of YOLO-Fish-1 and YOLO-Fish-2 models in underwater fish detection. Replicating the original YOLO-Fish scores encountered challenges with the models exhibiting an average precision substantially less than expected. A challenging dataset for fish detection was created using footage of Yellowfin Grouper spawning. The findings highlight challenges in underwater fish detection, specifically with sub optimal image quality.