International Journal of Advance Computational Engineering and Networking (IJACEN)
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Volume-7, Issue-9  ( Sep, 2019 )
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Statistics report
Nov. 2019
Submitted Papers : 80
Accepted Papers : 10
Rejected Papers : 70
Acc. Perc : 12%
Issue Published : 80
Paper Published : 1200
No. of Authors : 3014
  Journal Paper

Paper Title
Web And Personal Image Annotation By Mining Label Correlation With Relaxed Visual Graph Embedding

Abstract
Abstract-Image processing refers to processing of a 2D picture by a computer. An image may be considered to contain sub images. Now a day the number of digital images rapidly increases. There are unlabeled images available, for that our system assigns automatic image annotation. We propose a system for image annotation by integrating label correlation mining and visual similarity mining into a join framework. We first construct a training image database which includes image visual features. A multilabel classifier is then train by simultaneously uncovering the shared structure common to different labels and the visual graph embedded label prediction matrix for image annotation. We apply the proposed framework to both image annotation and personal album labeling using the NUS-WIDE image dataset.


Author - Prashant Sakunde, Abhishek Kakalij, Vishwajeet Mane, Nikhil Akade

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| Published on 2014-05-16
   
   
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