NDLI: Image retrieval based on augmented relational graph representation

Content Provider	Springer Nature Link
Author	Yang, Yu Bin Li, Ya Nan Pan, Ling Yan Li, Ning He, Guang Nan
Copyright Year	2012
Abstract	The “semantic gap” problem is one of the main difficulties in image retrieval tasks. Semi-supervised learning, typically integrated with the relevance feedback techniques, is an effective method to narrow down the semantic gap. However, in semi-supervised learning, the amount of unlabeled data is usually much greater than that of labeled data. Therefore, the performance of a semi-supervised learning algorithm relies heavily on its effectiveness of using the relationships between the labeled and unlabeled data. This paper proposes a novel algorithm to better explore those relationships by augmenting the relational graph representation built on the entire data set, expected to increase the intra-class weights while decreasing the inter-class weights and linking the potential intra-class data. The augmented relational matrix can be directly used in any semi-supervised learning algorithms. The experimental results in a range of feedback-based image retrieval tasks show that the proposed algorithm not only achieves good generality, but also outperforms other algorithms in the same semi-supervised learning framework.
Starting Page	489
Ending Page	501
Page Count	13
File Format	PDF
ISSN	0924669X
Journal	Applied Intelligence
Volume Number	38
Issue Number	4
e-ISSN	15737497
Language	English
Publisher	Springer US
Publisher Date	2012-08-12
Publisher Place	Boston
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Graph embedding Image retrieval Manifold learning Relevance feedback Artificial Intelligence (incl. Robotics) Mechanical Engineering Manufacturing, Machines, Tools
Content Type	Text
Resource Type	Article
Subject	Artificial Intelligence

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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