Seeded transfer learning for regression problems with deep learning

Salaken, Syed Moshfeq, Khosravi, Abbas, Nguyen, Thanh Thi and Nahavandi, Saeid 2019, Seeded transfer learning for regression problems with deep learning, Expert systems with applications, vol. 115, pp. 565-577, doi: 10.1016/j.eswa.2018.08.041.

Attached Files
Name Description MIMEType Size Downloads

Title Seeded transfer learning for regression problems with deep learning
Author(s) Salaken, Syed MoshfeqORCID iD for Salaken, Syed Moshfeq orcid.org/0000-0001-8632-2665
Khosravi, AbbasORCID iD for Khosravi, Abbas orcid.org/0000-0001-6927-0744
Nguyen, Thanh ThiORCID iD for Nguyen, Thanh Thi orcid.org/0000-0001-9709-1663
Nahavandi, SaeidORCID iD for Nahavandi, Saeid orcid.org/0000-0002-0360-5270
Journal name Expert systems with applications
Volume number 115
Start page 565
End page 577
Total pages 13
Publisher Elsevier
Place of publication Amsterdam, The Netherlands
Publication date 2019-01
ISSN 0957-4174
Keyword(s) Transfer learning
Domain adaptation
Science & Technology
Technology
Computer Science, Artificial Intelligence
Engineering, Electrical & Electronic
Operations Research & Management Science
Computer Science
Engineering
Language eng
DOI 10.1016/j.eswa.2018.08.041
Field of Research 080108 Neural, Evolutionary and Fuzzy Computation
01 Mathematical Sciences
08 Information and Computing Sciences
Socio Economic Objective 970109 Expanding Knowledge in Engineering
HERDC Research category C1 Refereed article in a scholarly journal
Copyright notice ©2018, Elsevier Ltd.
Persistent URL http://hdl.handle.net/10536/DRO/DU:30114066

Connect to link resolver
 
Unless expressly stated otherwise, the copyright for items in DRO is owned by the author, with all rights reserved.

Versions
Version Filter Type
Citation counts: TR Web of Science Citation Count  Cited 8 times in TR Web of Science
Scopus Citation Count Cited 7 times in Scopus
Google Scholar Search Google Scholar
Access Statistics: 113 Abstract Views, 5 File Downloads  -  Detailed Statistics
Created: Wed, 17 Oct 2018, 08:47:57 EST

Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au.