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Image Classification on Tiny ImageNet 64x64 (test)

29.6AccuracyNCFM
0.2727.88615.523.114Feb 28, 2025
Updated 8mo ago

Evaluation results

MethodLinks
NCFMIPC=50, Ratio (%)=10, Backbone=4-layer ConvNet2025.0229.6
MTTIPC=50, Ratio (%)=10, Backbone=4-layer ConvNet2025.0228
IDMIPC=50, Ratio (%)=10, Backbone=4-layer ConvNet2025.0227.7
NCFMIPC=10, Ratio (%)=2, Backbone=4-layer ConvNet2025.0226.8
ATTIPC=10, Ratio (%)=2, Backbone=4-layer ConvNet2025.0225.8
FrePoIPC=10, Ratio (%)=2, Backbone=4-layer ConvNet2025.0225.4
FTDIPC=10, Ratio (%)=2, Backbone=4-layer ConvNet2025.0224.5
DMIPC=50, Ratio (%)=10, Backbone=4-layer ConvNet2025.0224.1
MTTIPC=10, Ratio (%)=2, Backbone=4-layer ConvNet2025.0223.2
IDMIPC=10, Ratio (%)=2, Backbone=4-layer ConvNet2025.0221.9
NCFMIPC=1, Ratio (%)=0.2, Backbone=4-layer ConvNet2025.0218.2
HerdingIPC=50, Ratio (%)=10, Backbone=4-layer ConvNet2025.0216.7
FrePoIPC=1, Ratio (%)=0.2, Backbone=4-layer ConvNet2025.0215.4
RandomIPC=50, Ratio (%)=10, Backbone=4-layer ConvNet2025.0215
ForgettingIPC=50, Ratio (%)=10, Backbone=4-layer ConvNet2025.0215
DMIPC=10, Ratio (%)=2, Backbone=4-layer ConvNet2025.0212.9
ATTIPC=1, Ratio (%)=0.2, Backbone=4-layer ConvNet2025.0211
FTDIPC=1, Ratio (%)=0.2, Backbone=4-layer ConvNet2025.0210.4
IDMIPC=1, Ratio (%)=0.2, Backbone=4-layer ConvNet2025.0210.1
MTTIPC=1, Ratio (%)=0.2, Backbone=4-layer ConvNet2025.028.8
HerdingIPC=10, Ratio (%)=2, Backbone=4-layer ConvNet2025.026.3
ForgettingIPC=10, Ratio (%)=2, Backbone=4-layer ConvNet2025.025.1
RandomIPC=10, Ratio (%)=2, Backbone=4-layer ConvNet2025.025
DMIPC=1, Ratio (%)=0.2, Backbone=4-layer ConvNet2025.023.9
HerdingIPC=1, Ratio (%)=0.2, Backbone=4-layer ConvNet2025.022.8
ForgettingIPC=1, Ratio (%)=0.2, Backbone=4-layer ConvNet2025.021.6
RandomIPC=1, Ratio (%)=0.2, Backbone=4-layer ConvNet2025.021.4