UGC Approved Journal no 63975(19)

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

Volume 8 Issue 10
October-2021
eISSN: 2349-5162

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

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Published Paper ID:
JETIRFD06041


Registration ID:
315668

Page Number

269-273

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Title

Multiclass Apparel Identification Based on HOG Feature Extractor using SVM and Softmax

Abstract

Image classification and recognition plays an important role in many applications, like online shopping, driverless cars, automation, similar item retrieval queries, etc. In this project we have presented the identification of fashion items in an image. Given an image our model can identify whether it contains any fashion item or not. It can identify items like shirt, shoes, t-shirt, trousers, handbag and 6 other items. Our model consists of two things which are a feature extractor and a classifier. Based on research and experimental work we have selected HOG (Histogram of Oriented Gradients) as feature extraction method and two classifiers which are SVM (Support Vector Machine) and Softmax. It is a very tough task to select appropriate model for classification. It requires training and testing various models and techniques. However, we are able to achieve excellent results using our model.

Key Words

Multiclass Apparel Classification, Machine Learning, Object Identification, Image Classification, SVM Classifier, Softmax Classifier.

Cite This Article

"Multiclass Apparel Identification Based on HOG Feature Extractor using SVM and Softmax", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.8, Issue 10, page no.269-273, October-2021, Available :http://www.jetir.org/papers/JETIRFD06041.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

"Multiclass Apparel Identification Based on HOG Feature Extractor using SVM and Softmax", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.8, Issue 10, page no. pp269-273, October-2021, Available at : http://www.jetir.org/papers/JETIRFD06041.pdf

Publication Details

Published Paper ID: JETIRFD06041
Registration ID: 315668
Published In: Volume 8 | Issue 10 | Year October-2021
DOI (Digital Object Identifier):
Page No: 269-273
Country: -, -, India .
Area: Engineering
ISSN Number: 2349-5162
Publisher: IJ Publication


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