scholarly journals An Iris Recognition System Using Deep convolutional Neural Network

2020 ◽  
Vol 1530 ◽  
pp. 012159
Author(s):  
Maryim Omran ◽  
Ebtesam N. AlShemmary
2021 ◽  
Author(s):  
Wael Alnahari

Abstract In this paper, I proposed an iris recognition system by using deep learning via neural networks (CNN). Although CNN is used for machine learning, the recognition is achieved by building a non-trained CNN network with multiple layers. The main objective of the code the test pictures’ category (aka person name) with a high accuracy rate after having extracted enough features from training pictures of the same category which are obtained from a that I added to the code. I used IITD iris which included 10 iris pictures for 223 people.


Author(s):  
Sahana P. Savant ◽  
P. S. Khanagoudar

Recently it is found that people are becoming more cautious to their diet throughout the universe. Unhealthy diet can cause many problems like sugar, obesity, gain in weight and many other chronic health related issues. Essential part of our diet is contributed by fruits as they are rich source of vitamins,fiber,energy and nutrients. Today's era has been adapted to a system of intake of foods which has several adverse effects on human health. The proposed system is Autonomous Fruit Recognition system based on Deep Convolutional Neural Network (DCNN) method. Using this technology recognition and estimation of fruit calories is necessary to spread awareness about food habits among people suffering from obesity due to bad food culture and consumption of food .This proposed web/app based system simplifies the calorie measuring process of fruit. The machine learning based API used in our system recognize the fruit and provide calorie content of that fruit. System uses convolutional Neural Network called MobileNet. This web/app based application is user friendly.


Sign in / Sign up

Export Citation Format

Share Document