A Data-centric Approach to Class-specific Bias in Image Data Augmentation: Appendices A-L
2024-9-1 02:0:22
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Authors:
(1) Athanasios Angelakis, Amsterdam University Medical Center, University of Amsterdam - Data Science Center, Amsterdam Public Health Research Institute, Amsterdam, Netherlands
(2) Andrey Rass, Den Haag, Netherlands.
Table of Links
Appendices
Appendix A: Image dimensions (in pixels) off training images after being randomly cropped and before being resized
[32x32, 31x31, 30x30,
29x29, 28x28, 27x27,
26x26, 25x25, 24x24,
22x22, 21x21, 20x20,
19x19, 18x18, 17x17,
16x16, 15x15, 14x14,
13x13, 12x12, 11x11,
10x10, 9x9, 8x8,
6x6,5x5, 4x4, 3x3]
Appendix B: Dataset samples corresponding to the Fashion-MNIST segment used in training
Appendix C: Dataset samples corresponding to the CIFAR-10 segment used in training
Appendix D: Dataset samples corresponding to the CIFAR-100 segment used in training
Appendix E: Full collection of class accuracy plots for CIFAR-100
Without Random Horizontal Flip:
With Random Horizontal Flip
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