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  This model is a garbage classification system built on the ResNet50 architecture, fine-tuned for classifying household garbage into 12 distinct categories: paper, cardboard, biological, metal, plastic, green-glass, brown-glass, white-glass, clothes, shoes, batteries, and trash. The model was trained on a dataset sourced from the Kaggle Garbage Classification Dataset by Mostafa Abla. The purpose of this model is to assist in sorting household waste for better recycling efficiency.
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  ## Model Architecture
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- Base Model: ResNet50 (pre-trained on ImageNet)
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  Modifications: The final fully connected layer was modified to output 12 classes instead of the default 1000 classes used in ImageNet.
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  ## Intended Use
 
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  This model is a garbage classification system built on the ResNet50 architecture, fine-tuned for classifying household garbage into 12 distinct categories: paper, cardboard, biological, metal, plastic, green-glass, brown-glass, white-glass, clothes, shoes, batteries, and trash. The model was trained on a dataset sourced from the Kaggle Garbage Classification Dataset by Mostafa Abla. The purpose of this model is to assist in sorting household waste for better recycling efficiency.
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  ## Model Architecture
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+ Base Model: ResNet50 (pre-trained on ImageNet).
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  Modifications: The final fully connected layer was modified to output 12 classes instead of the default 1000 classes used in ImageNet.
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  ## Intended Use