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Automated Attendance System using Machine Learning Approach

Author(s):

Amey Shirke , Suman Ramesh Tulsiani Technical Campus; Soham Dunahe, Suman Ramesh Tulsiani Technical Campus; Omkar Wagh, Suman Ramesh Tulsiani Technical Campus; Vivek Shrivastav, Suman Ramesh Tulsiani Technical Campus; Prof. Bhushan Mahajan, Suman Ramesh Tulsiani Technical Campus

Keywords:

Face Recognition, Principal Component Analysis, Voice Conversion, SIFT

Abstract

Limited functionality of face detection algorithm are still facing problems in real environment. This problem is marked as Sparse Fingerprint Classification Algorithm (SFCA). There are two phases training and testing. Parts of images are obtained in training phase and in testing phase every part of image is converted into binary sparse format. The binary representation marks for their respective categories and maximum marked category decides the identity of the image. SFCA works efficient when the size of data file is limited.

Other Details

Paper ID: IJSRDV5I90006
Published in: Volume : 5, Issue : 9
Publication Date: 01/12/2017
Page(s): 24-26

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