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Multi-Label Classification of a Scene Image using Fuzzy Logic

Published on March 2017 by Janhavi Shirke, N. M. Shahane
Emerging Trends in Computing
Foundation of Computer Science USA
ETC2016 - Number 2
March 2017
Authors: Janhavi Shirke, N. M. Shahane

Janhavi Shirke, N. M. Shahane . Multi-Label Classification of a Scene Image using Fuzzy Logic. Emerging Trends in Computing. ETC2016, 2 (March 2017), 4-10.

author = { Janhavi Shirke, N. M. Shahane },
title = { Multi-Label Classification of a Scene Image using Fuzzy Logic },
journal = { Emerging Trends in Computing },
issue_date = { March 2017 },
volume = { ETC2016 },
number = { 2 },
month = { March },
year = { 2017 },
issn = 0975-8887,
pages = { 4-10 },
numpages = 7,
url = { /proceedings/etc2016/number2/27307-6260/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
%0 Proceeding Article
%1 Emerging Trends in Computing
%A Janhavi Shirke
%A N. M. Shahane
%T Multi-Label Classification of a Scene Image using Fuzzy Logic
%J Emerging Trends in Computing
%@ 0975-8887
%V ETC2016
%N 2
%P 4-10
%D 2017
%I International Journal of Computer Applications

A natural scene image contains object categories which form ambiguous boundaries. Measuring this ambiguitywhile classifying an image, is a challenging task. A scene image belongs to multiple categories at a time which makes a task of classification multi label one. Binary classification fails to capture this ambiguity while classifying the scene image into one of mutually exclusive classes. This problem can be handled by applying fuzzy logic with non-mutually exclusive class categories. This project work provides a ranking based on class membership instead of binary classification.

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Index Terms

Computer Science
Information Sciences


Fuzzy Logic Binary Classification Ranking