Deep Learning, Artificial Intelligence, Semi Supervised Learning, Image Classification, Data Augmentation.
used where each ^U1 image is rotated and the model needs to predict the rotation amount. In total, the ReMixMatch loss is: In practice, λr=λ^U1=0.5. λU=1.5. T=0.5 for sharpening, and Beta=0.75 for mixup. K=8. The final model as an exponential moving average over the trained model weights with a