Visual Transfer Learning: Informal Introduction and Literature Overview

TL;DR

This paper provides an informal introduction and literature overview of transfer learning techniques in visual recognition, emphasizing their importance for small datasets and rapid generalization.

Contribution

It offers a comprehensive overview of existing transfer learning methods in visual recognition, serving as foundational background for further research.

Findings

Transfer learning improves performance on small datasets

Various methods exist for visual transfer learning

Transfer learning enables quick generalization from limited data

Abstract

Transfer learning techniques are important to handle small training sets and to allow for quick generalization even from only a few examples. The following paper is the introduction as well as the literature overview part of my thesis related to the topic of transfer learning for visual recognition problems.