Paper accepted by Machine Vision and Application (Springer)
Published:
Our paper “Semi-supervised Learning using Adversarial Training with Good and Bad Samples” has been accepted by Machine Vision and Application (Springer). In this study, we combine good synthetic images and bad images (complementary data) to boost image classification accuracy in semi-supervised learning scenario. Read More