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Image retrieval using latent feature learning by deep architecture
Garg N, Nikhitha P,
Published in IEEE
The explosive growth of data, images in the World Wide Web makes it critical to the information retrievals. Image retrieval has been recognized as an elementary problem in the retrieval tasks and this exercise has got a wide attention based on the underlying domain characteristics. For instance, in social media data encompasses of noisy, diverse, heterogeneous, interconnected data. To confront these numerous characteristics and employ image retrieval the widely accepted deep architecture concept is utilized with the help of natural language latent query features. In this paper, we are introducing a novel approach for image retrieval task which collaboratively make use of the technicalities of natural language processing and deep architecture. © 2014 IEEE.
About the journal
JournalData powered by Typeset2014 IEEE International Conference on Computational Intelligence and Computing Research
PublisherData powered by TypesetIEEE
Open Access0