Few Shot Image Classification On Omniglot 1 2
Metrics
Accuracy
Results
Performance results of various models on this benchmark
Model Name | Accuracy | Paper Title | Repository |
---|---|---|---|
iMAML, Hessian-Free | 99.50 | - | - |
Matching Nets | 98.1 | - | - |
Relation Net | 99.6 | - | - |
MAML++ | 99.47 | - | - |
MAML | 98.7 | - | - |
adaCNN (DF) | 98.42 | - | - |
VAMPIRE | 98.43 | - | - |
DCN4 | 99.8% | - | - |
Prototypical Networks | 98.8 | - | - |
MT-net | 99.5 | - | - |
ConvNet with Memory Module | 98.4 | - | - |
APL | 97.9 | - | - |
MC2+ | 99.97 | - | - |
Hyperbolic ProtoNet | 99.0 | - | - |
Neural Statistician | 98.1 | - | - |
Reptile + Transduction | 97.68 | - | - |
DCN6-E | 99.92% | - | - |
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