International Journal of Electrical, Electronics and Data Communication (IJEEDC)
eISSN:2320-2084 , pISSN:2321-2950
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Feb. 2024
Submitted Papers : 80
Accepted Papers : 10
Rejected Papers : 70
Acc. Perc : 12%
Issue Published : 131
Paper Published : 1705
No. of Authors : 4719
  Journal Paper

Paper Title :
A CNN Way of IRIS Recognition using AlexNet

Author :Vıshalakshı Rıturaj, Shyam Krıshna Sıngh

Article Citation :Vıshalakshı Rıturaj ,Shyam Krıshna Sıngh , (2021 ) " A CNN Way of IRIS Recognition using AlexNet " , International Journal of Electrical, Electronics and Data Communication (IJEEDC) , pp. 17-21, Volume-9,Issue-11

Abstract : Abstract - It is very obvious and natural to identify a person on the basis of his/her biological trait and we do it since our birth. But now, we came to know how our brain does this activity. Iris has always been one of the most precious, trusted and accurate means of recognition due to its unique and ageless features. Traditional approach of iris recognition system had to face a lot of problems in image capturing, pre-processing and extracting features. But now, Artificial Intelligence is the new boss and it has brought a revolution by introducing Convolutional Neural network, which possesses a resemblance to the human brain. This paper has made use of a pre-trained model of CNN, namely AlexNet, for feature extraction, which automatically extracts a huge matrix of features. These features were passed in SVM (Support Vector Machine) classification to classify images among the correct classes. I have preferred to use iris database obtained from IITD to conduct the research. Keywords - Support Vector Machine (SVM), Convolutional Neural Network (CNN), Biometrics, Feature extraction, Recognition, Classification

Type : Research paper

Published : Volume-9,Issue-11


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