This project utilizes ensemble learning models to classify underwater images effectively, addressing challenges like low visibility and distortions. By leveraging techniques that combine the strengths of multiple algorithms, it aims to enhance accuracy and reliability for applications in marine biodiversity studies, ecological assessments, and underwater environmental monitoring.
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