Speed, time and safety are of great importance in many operations conducted today. There are standards such as ISO 27001, ITIL (Information Technologies Infrastructure Library), COBIT (Control Objectives for Information and Related Technology), which are globally recognized not only regarding access to information and the use of information but also information retention. Governmental institutions and many large companies use fingerprint, card reading, iris recognition and facial recognition systems in entrances and exits, regarding the protection of information.The facial recognition system application developed within the scope of this study performs the facial recognition by using Convolutional Neural Networks (CNN), which is one of the deep learning algorithms and restricts the use of your personal computer by people you do not know. In addition to this restriction, it takes a photo of the person who wants to use your personal computer and sends this photo to the mobile phone of the owner of the computer, who was previously defined in the system and informs him/her.Regarding the testing of the face recognition system application FEI (Faculdade de Engenharia Industrial- Faculty of Industrial Engineering) facial database was used. In this facial database, there are 14 different poses of 200 people (one is neutral, one is smiling, one is not smiling, and the others are at different angles). Trials were made to access the system with a total of 2800 photographs and as a result of the trials, success was achieved with a ratio of 76.31% in the worst angle and light and a ratio of 99.15% in the best angle and light.
: 20 Nisan 2020
|APA||Ayata, F , Çavuş, H , İnan, M , Seyyarer, E , Bi̇çek, E , Kına, E . (2020). Dostroajan: Facial Recognition Based System Input Control Agent . AJIT-e: Bilişim Teknolojileri Online Dergisi , 11 (40) , 82-96 . DOI: 10.5824/ajite.2020.01.005.x|