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This project was implemented for a Kaggle competition (see link in repo's details). The goal was to classify food photos by using a training set of ~30.000 images. After experimentation with different models like VGG16 and ResNet CNNs, the final decision was to use transfer learning with ResNet50 achieving 61% top-1 accuracy.
AntonisKl/Food-Image-Classification
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This project was implemented for a Kaggle competition (see link in repo's details). The goal was to classify food photos by using a training set of ~30.000 images. After experimentation with different models like VGG16 and ResNet CNNs, the final decision was to use transfer learning with ResNet50 achieving 61% top-1 accuracy.
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- Jupyter Notebook 64.7%
- Python 35.3%