Abstract
Recently, contrastive learning has shown its effectiveness in self-supervised learning by training features of augmentations of input images based on the contrastive loss. This paper aims to introduce contrastive learning and discuss the effects of augmentations, features, and parameters of contrastive learning. Interactive figures are developed to demonstrate the effective schemes proposed in contrastive learning and can be accessed on IEEE Xplore.
Original language | English |
---|---|
Pages (from-to) | 79-80 |
Number of pages | 2 |
Journal | IEEE Computational Intelligence Magazine |
Volume | 19 |
Issue number | 1 |
DOIs | |
State | Published - 1 Feb 2024 |