INTERNATIONAL JOURNAL OF SCIENTIFIC DEVELOPMENT AND RESEARCH International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2455-2631 | Impact factor: 8.15 | ESTD Year: 2016
open access , Peer-reviewed, and Refereed Journals, Impact factor 8.15
EFFICIENT TWINS IDENTIFICATION AND CLASSIFICATION USING MACHINE LEARNING
Authors Name:
B. PURUSOTHAM
, G. Mahesh , G. Bhanu Prakash , B. SaiRam , Dr P. Rama
Unique Id:
IJSDR2304291
Published In:
Volume 8 Issue 4, April-2023
Abstract:
The main concept of our work is to develop an identical twin detection approach that increases the accuracy of classification and identification using a class of convolutional neural networks (CNN). Our method is based on the observation that twins have similar facial features. Trained with CNN to learn the facial features. A general face recognition model is developed based on a system comprising several features or attributes. Face detection, feature extraction, and face recognition are the key steps in any twin detection process of twins. Then trained with CNN to extract the facial features of an input image. It is applicable to all image data sets. We have conducted experiments on a publicly available twin dataset, and the result of this method shows that this method can achieve high accuracy. In our project, we have used algorithms such as Decision Tree (DT) and Convolution Neural Network (CNN) in terms of accuracy.
Keywords:
Decision Tree (DT) and Convolution Neural Network(CNN)
Cite Article:
"EFFICIENT TWINS IDENTIFICATION AND CLASSIFICATION USING MACHINE LEARNING", International Journal of Science & Engineering Development Research (www.ijsdr.org), ISSN:2455-2631, Vol.8, Issue 4, page no.1884 - 1887, April-2023, Available :http://www.ijsdr.org/papers/IJSDR2304291.pdf
Downloads:
000337062
Publication Details:
Published Paper ID: IJSDR2304291
Registration ID:205527
Published In: Volume 8 Issue 4, April-2023
DOI (Digital Object Identifier):
Page No: 1884 - 1887
Publisher: IJSDR | www.ijsdr.org
ISSN Number: 2455-2631
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