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What is Live Fish Species Classification in Underwater Ima about?

This document summarizes a research article that proposes using convolutional neural networks (CNNs) and incremental learning for live reef fish species classification in underwater images. The researchers train their CNN model progressively by first focusing on learning difficult species well, then gradually learning new species while maintaining performance on old species. They achieve an accuracy of 81.83% on a benchmark dataset using their proposed approach. The document provides background on challenge

Author

abourifa hanane

Language

EN