This project showcases the InceptionV3 model, which is a deep CNN architecture designed for efficient image classification. InceptionV3 uses a novel approach with multiple filter sizes in a single layer to capture features at different scales. The repository provides a comprehensive implementation of InceptionV3, along with pre-trained models on ImageNet. The project includes custom training scripts, fine-tuning methods, and evaluation techniques, such as accuracy, precision, recall, and F1-score.
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