A Review of Deep Transfer Learning and Recent Advancements

Understand

Deep learning has been the answer to many machine learning problems during the past two decades.

• However, it comes with two major constraints: dependency on extensive labeled data and training costs.
• Transfer learning in deep learning, known as Deep Transfer Learning (DTL), attempts to reduce such dependency and costs by reusing an obtained knowledge from a source data/task in training on a target data/task.
• Most applied DTL techniques are network/model-based approaches.