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Erschienen in:
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2018 | OriginalPaper | Buchkapitel

A Survey on Deep Transfer Learning

verfasst von : Chuanqi Tan, Fuchun Sun, Tao Kong, Wenchang Zhang, Chao Yang, Chunfang Liu

Erschienen in: Artificial Neural Networks and Machine Learning – ICANN 2018

Verlag: Springer International Publishing

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Abstract

As a new classification platform, deep learning has recently received increasing attention from researchers and has been successfully applied to many domains. In some domains, like bioinformatics and robotics, it is very difficult to construct a large-scale well-annotated dataset due to the expense of data acquisition and costly annotation, which limits its development. Transfer learning relaxes the hypothesis that the training data must be independent and identically distributed (i.i.d.) with the test data, which motivates us to use transfer learning to solve the problem of insufficient training data. This survey focuses on reviewing the current researches of transfer learning by using deep neural network and its applications. We defined deep transfer learning, category and review the recent research works based on the techniques used in deep transfer learning.

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Metadaten
Titel
A Survey on Deep Transfer Learning
verfasst von
Chuanqi Tan
Fuchun Sun
Tao Kong
Wenchang Zhang
Chao Yang
Chunfang Liu
Copyright-Jahr
2018
Buch
Artificial Neural Networks and Machine Learning – ICANN 2018

Print ISBN: 978-3-030-01423-0

Electronic ISBN: 978-3-030-01424-7

Copyright-Jahr: 2018

DOI
https://doi.org/10.1007/978-3-030-01424-7_27