Transfer of Pretrained Model Weights Substantially Improves Semi-Supervised Image Classification

2 code implementations • 2 Sep 2021 • Attaullah Sahito, Eibe Frank, Bernhard Pfahringer

Deep neural networks produce state-of-the-art results when trained on a large number of labeled examples but tend to overfit when small amounts of labeled examples are used for training.

Metric Learning Self-Learning +2

Better Self-training for Image Classification through Self-supervision

3 code implementations • 2 Sep 2021 • Attaullah Sahito, Eibe Frank, Bernhard Pfahringer

Self-training is a simple semi-supervised learning approach: Unlabelled examples that attract high-confidence predictions are labelled with their predictions and added to the training set, with this process being repeated multiple times.

Classification Image Classification

Semi-Supervised Learning using Siamese Networks

2 code implementations • 2 Sep 2021 • Attaullah Sahito, Eibe Frank, Bernhard Pfahringer

This work explores a new training method for semi-supervised learning that is based on similarity function learning using a Siamese network to obtain a suitable embedding.