ViTSGMM: A Robust Semi-Supervised Image Recognition Network Using Sparse Labels

Benchmark Model Rank Results
semi-supervised-image-classification-on-cifar-10-250-labelsSemiOccam#1Percentage error: 3.47
semi-supervised-image-classification-on-cifar-10-40-labelsSemiOccam#1Percentage error: 3.51
semi-supervised-image-classification-on-cifar-100-2500-labelsSemiOccam#1Percentage error: 22.19
semi-supervised-image-classification-on-cifar-100-400-labelsSemiOccam#3Percentage error: 26.59
semi-supervised-image-classification-on-stl-10-40-labelsSemiOccam#1Accuracy: 95.43