A Survey on Deep Transfer Learning
Abstrak
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.
Topik & Kata Kunci
Penulis (6)
Chuanqi Tan
F. Sun
Tao Kong
Wenchang Zhang
Chao Yang
Chunfang Liu
Akses Cepat
PDF tidak tersedia langsung
Cek di sumber asli →- Tahun Terbit
- 2018
- Bahasa
- en
- Total Sitasi
- 2865×
- Sumber Database
- Semantic Scholar
- DOI
- 10.1007/978-3-030-01424-7_27
- Akses
- Open Access ✓