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(e.g., ImageNet, a local project, or a specific website?)

The rise of deep learning relies on massive datasets where individual image quality and annotation accuracy are often assumed rather than verified. 148_1000.jpg

Testing how minor augmentations (rotations, color jitters) to this image change the model's confidence. 4. Conclusion a local project

Recommendations for automated "cleaning" of datasets based on high-loss samples. 148_1000.jpg

Generating Grad-CAM visualizations to identify which pixels the model focuses on when classifying this specific image. 3. Results & Discussion