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OceanNet

This repository contains the implementation of a deep learning model designed to classify sargassum density into five categories: none, low, moderate, abundant, and excessive. Utilizing a ResNet-based convolutional neural network (CNN) and PyTorch, this project leverages GPU acceleration via CUDA for efficient training on image datasets.

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This repository contains the implementation of a deep learning model designed to classify sargassum density into five categories: none, low, moderate, abundant, and excessive. Utilizing a ResNet-based convolutional neural network (CNN) and PyTorch, this project leverages GPU acceleration via CUDA for efficient training on image datasets.

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