International Journal of Emerging Trends & Technology in Computer Science
A Motivation for Recent Innovation & Research
ISSN 2278-6856
www.ijettcs.org

Call for Paper, Published Articles, Indexing Infromation Unsupervised Learning of Semantic Classes for Image Mining, Authors : K Rajendra Prasad, International Journal of Emerging Trends & Technology in Computer Science (IJETTCS), www.ijettcs.org
Volume & Issue no: Volume 6, Issue 4, July - August 2017

Title:
Unsupervised Learning of Semantic Classes for Image Mining
Author Name:
K Rajendra Prasad
Abstract:
Abstract Scalability is one of key aspect to effective use of retrieval of image annotation in image mining. Exploiting semantic relations can significantly improve the scalability of SIMM for large-scale datasets. The overall performance of proposed SIMM is compared with two exiting methods, k-means and spectral clustering with fuzzy concepts. Efficiency of SIMM is demonstrated with two parameters, accuracy and normalized mutual information on real world image databases during experimental study. The objective is to learn fine-grained distinctions among images and produce a fuzzy based similarity score for developing an effective Semantic based Image-Mining Method (SIMM). Keywords:Image annotation, semantic map, fuzzy concept, PSA, SIMM
Cite this article:
K Rajendra Prasad , " Unsupervised Learning of Semantic Classes for Image Mining " , International Journal of Emerging Trends & Technology in Computer Science (IJETTCS), Volume 6, Issue 4, July - August 2017 , pp. 088-090 , ISSN 2278-6856.
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