(e.g., Computer Science, Art History, or Forensics?)
Testing how minor augmentations (rotations, color jitters) to this image change the model's confidence. 4. Conclusion 148_1000.jpg
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
Recommendations for automated "cleaning" of datasets based on high-loss samples. 148_1000.jpg