Transfer robust sparse coding based on graph and joint distribution adaption for image representation

Transfer learning can transfer knowledge from a source domain to a target domain, promoting the performance of the model learned from the source data. Sparse coding can make the representation of a model more succinct and easy to manipulate. Existing transfer sparse coding methods assume the data fr...

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Bibliographic Details
Published in:	Knowledge-based systems Vol. 147; pp. 1 - 11
Main Authors:	Zhao, Peng, Wang, Wei, Lu, Yijuan, Liu, Huiting, Yao, Sheng
Format:	Journal Article
Language:	English
Published:	Amsterdam Elsevier B.V 01.05.2018 Elsevier Science Ltd
Subjects:	Algorithms Artificial intelligence Coding Data Distribution Experiments Graphical representations Image representation Information dissemination Knowledge management Knowledge sharing Learning Noise Representation Robustness Sparse coding Transfer learning Image representation Sparse coding Transfer learning
ISSN:	0950-7051, 1872-7409
Online Access:	Get full text
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