In this repo, I perform dataset condensation via distrbution matching (https://github.com/VICO-UoE/DatasetCondensation), without differentiable siamese augmentation, on MRI classification dataset (https://www.kaggle.com/datasets/sartajbhuvaji/brain-tumor-classification-mri)
Conensation of Whole Unbalanced Dataset
Running Time (seconds) |
Accuracy over Real Training |
Accuracy over Real Testing |
Condensed Images per Class |
676.7407 |
43.0662 |
29.9492 |
10 |
Condensation of Balanced Dataset
Running Time (seconds) |
Accuracy over Real Training |
Accuracy over Real Testing |
Condensed Images per Class |
649.1408 |
25.1282 |
20.3046 |
10 |
Condensation of 20 MRI images/class into 2 images/class
Running Time (seconds) |
Accuracy over Real Training |
Accuracy over Real Testing |
Condensed Images per Class |
311.9385 |
52.5 |
27.4112 |
2 |