Few Shot Image Classification On Caltech 256
Metrics
Accuracy
Results
Performance results of various models on this benchmark
Model Name | Accuracy | Paper Title | Repository |
|---|---|---|---|
| MergedNet-Max | 65.77 | MergedNET: A simple approach for one-shot learning in siamese networks based on similarity layers | |
| UL-Hopfield (ULH) | 74.7 | Unsupervised Learning using Pretrained CNN and Associative Memory Bank | - |
| Delta-encoder | 73.2 | Delta-encoder: an effective sample synthesis method for few-shot object recognition |
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