InfoMatch: Entropy Neural Estimation for Semi-Supervised Image Classification

arXiv:2404.11003v1 Announce Type: new
Abstract: Semi-supervised image classification, leveraging pseudo supervision and consistency regularization, has demonstrated remarkable success. However, the ongoing challenge lies in fully exploiting the potential of unlabeled data. To address this, we employ information entropy neural estimation to harness the potential of unlabeled samples. Inspired by contrastive learning, the entropy is estimated by maximizing a lower bound on mutual information across different augmented views. Moreover, we theoretically analyze that the information entropy of the posterior of an …

abstract arxiv challenge classification cs.cv data entropy harness however image information lies regularization samples semi-supervised success supervision type