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Title | Discriminant face features extraction, analysis & its application in multipose face recognization: a survey |
Authors |
Shekapure, S.S.
Kadam, N.V. |
ORCID | |
Keywords |
face recognition розпізнавання обличчя распознавание лица machine learning машинне навчання машинное обучение support vector machine classification класифікація классификация genetic algorithm генетичний алгоритм генетический алгоритм |
Type | Conference Papers |
Date of Issue | 2017 |
URI | http://essuir.sumdu.edu.ua/handle/123456789/55763 |
Publisher | |
License | |
Citation | Shekapure, S.S. Discriminant face features extraction, analysis & its application in multipose face recognization: a survey [Текст] / S.S. Shekapure, N.V. Kadam // Advanced Information Systems and Technologies : proceedings of the V international scientific conference, Sumy, May 17-19 2017/ Edited by S.І. Protsenko, V.V. Shendryk. - Sumy : Sumy State University, 2017. - P. 98-100. |
Abstract |
As one of the excellent learning and
classification performance, SVM and ISVM has become a
research topic in the field of machine learning and has been
applied in many areas, such as face detection and
recognition, handwriting automatic identification and
automatic text categorization. Face recognition is a
challenging computer vision problem. Given a face
database, goal of face recognition is to compare the input
image class with all the classes and then declare a decision
that identifies to whom the input image class belongs to or if
it doesn’t belong to the database at all. In this survey, we
study face recognition as a pattern classification problem.In
this paper, we study the concept of SVM and sophisticated
classification techniques for face recognition using the SVM
and ISVM along with the advantages and disadvantages.
This paper not only provides an up-to-date critical survey of
machine learning techniques but also performance analysis
of various SVM and ISVM techniques for face recognition
are compared. |
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