IJMTES – IMPROVING THE COMPETENCE OF INADEQUATELY LABELED IMAGES IN WEBSITE

Journal Title : International Journal of Modern Trends in Engineering and Science

Paper Title : IMPROVING THE COMPETENCE OF INADEQUATELY LABELED IMAGES IN WEBSITE

Author’s Name : Dineshbabu S | Gobalakrishnan M
unnamed

Volume 04 Issue 07 2017

ISSN no:  2348-3121

Page no: 23-26

Abstract – In current development of digital media numeral of human being facial images existing in the collective websites, a number of similes are suitably tagged other than a lot of of images are not tagged suitably, for that to defeat this difficulty an picture is in use as an participation and based on the facial appearance the related images are extracted. Then those descriptions are annotated properly. Now, we recommend a useful unsupervised label refinement (ULR) approach for cultivating the labels of mesh facial images using device learning technique. The results showed that the projected ULR algorithms can appreciably increase the act of the scheme.

Keywords – Content-Based Image Retrieval (CBIR), Weak Label, Search Based Face Annotation, Label Refinement, Annotation-Based Image Retrieval (ABIR)

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