MergedNET: A simple approach for one-shot learning in siamese networks based on similarity layers

Benchmark Model Rank Results
few-shot-image-classification-on-caltech-256-5-way-1-shotMergedNet-Max#2Accuracy: 65.77
few-shot-image-classification-on-cub-200-5-way-1-shotMergedNet-Max#23Accuracy: 75.34
few-shot-image-classification-on-cub-200-5-way-5-shotMergedNet-Max#25Accuracy: 83.42
few-shot-image-classification-on-mini-imagenet-5-way-1-shotMergedNet-Max#38Accuracy: 68.05
few-shot-image-classification-on-mini-imagenet-5-way-5-shotMergedNet-Max#47Accuracy: 80.40