Volume 15, Issue 1 (Special Issue on AI in ICT 2023)                   2023, 15(1): 16-23 | Back to browse issues page

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Navid Mahmoudabadi N, Afshar Kazemi M A, Radfar R, Amin Mousavi S A. A New Fuzzy Convolutional Neural Network for Face Recognition to Classify Authorized and Unauthorized Persons. International Journal of Information and Communication Technology Research 2023; 15 (1) :16-23
URL: http://ijict.itrc.ac.ir/article-1-507-en.html
1- Department of Information Technology Management Qeshm branch, Islamic Azad University Qeshm,Iran n.mahmoodabadi@gmail.com
2- Department of Industrial Management, Central Tehran Branch, Islamic Azad University, Tehran, Iran , dr.mafshar@gmail.com
3- Department of Industrial Management, Islamic Azad University, Science and Research Branch, Tehran, Iran
4- Department of Information Technology Management, Islamic Azad University, Science and Research Branch, Tehran, Iran
Abstract:   (284 Views)

Deep learning methods use neural networks that try to discover patterns within the image without human intervention and to learn that. One of the most popular algorithms in this field is the convolutional neural network algorithm. This algorithm uses several layers to receive the input image and process it so that the class label can be found. These layers are mostly based on Neural Networks. This research aims to provide a model of neural-fuzzy, based on convolutional neural network algorithm. In this research, we use the positive advantages of deep learning methods and fuzzy inference systems and present a new model of their application to Classify authorized and unauthorized Persons. For this purpose, we designed new neural-fuzzy layers to pass the image through them and finally classify each image. The results of the implementation of the above model show the efficiency and success of this system.

Article number: 2
Full-Text [PDF 800 kb]   (183 Downloads)    
Type of Study: Research | Subject: Information Technology

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