UGC Approved Journal no 63975

ISSN: 2349-5162 | ESTD Year : 2014
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Published in:

Volume 5 Issue 7
July-2018
eISSN: 2349-5162

UGC and ISSN approved 7.95 impact factor UGC Approved Journal no 63975

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Published Paper ID:
JETIRC006335


Registration ID:
184655

Page Number

153-159

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Title

COMPARISON OF CBIR TECHNIQUES: SVM, NEURAL NETWORK AND FUZZY LOGIC.

Abstract

Content Based Image Retrieval[CBIR] is also known as Query based image retrieval . CBIR is the use to recovering the image for finding a particular image from database of image. The paper discusses about the different technique’s working of CBIR SVM, neural networks and fuzzy logic. These techniques are extensively used for retrieval of images which have similar texture, shape and color features to the input image. The paper also discuss on comparing these techniques.

Key Words

CBIR, SVM [Support Vector Machine], Fuzzy Logic, Neural Network

Cite This Article

"COMPARISON OF CBIR TECHNIQUES: SVM, NEURAL NETWORK AND FUZZY LOGIC.", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.5, Issue 7, page no.153-159, July-2018, Available :http://www.jetir.org/papers/JETIRC006335.pdf

ISSN


2349-5162 | Impact Factor 7.95 Calculate by Google Scholar

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 7.95 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Cite This Article

"COMPARISON OF CBIR TECHNIQUES: SVM, NEURAL NETWORK AND FUZZY LOGIC.", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.5, Issue 7, page no. pp153-159, July-2018, Available at : http://www.jetir.org/papers/JETIRC006335.pdf

Publication Details

Published Paper ID: JETIRC006335
Registration ID: 184655
Published In: Volume 5 | Issue 7 | Year July-2018
DOI (Digital Object Identifier):
Page No: 153-159
Country: -, -, - .
Area: Engineering
ISSN Number: 2349-5162


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