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Reducing overfitting and improving generalization in training convolutional neural network under limited sample sizes in image recognition
Thanapol, Panissara; Lavangnananda, Kittichai; Bouvry, Pascal et al.
2020In 5th International Conference on Information Technology, Bangsaen 21-22 October 2020
Peer reviewed
 

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InCIT2020 Submission (Final Manuscript - IEEE eXpress checked) - Paper No. 1570661319.pdf
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Disciplines :
Computer science
Author, co-author :
Thanapol, Panissara ;  University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Computer Science (DCS)
Lavangnananda, Kittichai;  King Mongkut’s University of Technology Thonburi (Bangkok) > School of Information Technology
Bouvry, Pascal ;  University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Computer Science (DCS)
Pinel, Frederic ;  University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Computer Science (DCS)
Leprevost, Franck ;  University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Computer Science (DCS)
External co-authors :
yes
Language :
English
Title :
Reducing overfitting and improving generalization in training convolutional neural network under limited sample sizes in image recognition
Publication date :
2020
Event name :
5th International Conference on Information Technology - InCIT2020
Event organizer :
Association of Council of IT Deans (CITT)
Event place :
Bangsaen, Thailand
Event date :
from 21-10-2020 to 22-10-2020
Audience :
International
Main work title :
5th International Conference on Information Technology, Bangsaen 21-22 October 2020
Pages :
300-305
Peer reviewed :
Peer reviewed
Focus Area :
Computational Sciences
Available on ORBilu :
since 15 December 2020

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