scholarly journals Dostroajan: Facial Recognition Based System Input Control Agent

2020 ◽  
Vol 11 (40) ◽  
pp. 82-96
Author(s):  
Faruk AYATA ◽  
Hayati ÇAVUŞ ◽  
Mevlüt İNAN ◽  
Ebubekir SEYYARER ◽  
Emre BİÇEK ◽  
...  
Keyword(s):  
Personal Computer ◽  
System Application ◽  
Information Technologies ◽  
Iris Recognition ◽  
Facial Recognition ◽  
Recognition System ◽  
Control Agent ◽  
Information Retention ◽  
Governmental Institutions ◽  
Facial Recognition System

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.

scholarly journals SOME PROBLEMS OF USING THE FACIAL RECOGNITION SYSTEM IN LAW ENFORCEMENT ACTIVITIES

2021 ◽  
Vol 17 (1(63)) ◽  
pp. 189-200
Author(s):  
Василий Васильевич ЯРОВЕНКО ◽  
Галина Михайловна ШАПОВАЛОВА ◽  
Ринат Альбертович ИСМАГИЛОВ
Keyword(s):  
Face Recognition ◽  
Law Enforcement ◽  
Information Technologies ◽  
Facial Recognition ◽  
Recognition System ◽  
State Regulation ◽  
Private Life ◽  
Dialectical Logic ◽  
Advantages And Disadvantages ◽  
Facial Recognition System

The article draws attention to the problems of the use of modern software and hardware tools and methods of facial fixing and recognizing by law enforcement agencies. In using various techniques aimed at obtaining information on a person’s physiological and biological characteristics, it is important to respect not only his or her right to protect the data, but also state interests in combating crime (terrorism, corruption). Important factors are state regulation and the development of norms for the effective use of information technologies, telecommunications and artificial intelligence technologies so that citizens do not doubt their effectiveness and legitimacy. Purpose: to analyze current problems of combating crime; to submit proposals for improving the application of the facial recognition system, and the establishment by the Ministry of Internal Affairs of a single biometric database of Russians with the strictest compliance with citizens' constitutional rights to privacy, reliable protection of their personal data. Methods: the authors use empirical methods of comparison, description, interpretation as well as theoretical methods of formal and dialectical logic. Results: the study reveals the problems of using the facial recognition system, the advantages and disadvantages of the system are analyzed. On the one hand, in the Russian Federation there are no clear instructions and an algorithm for the use of face-recognition cameras, which would satisfy society’s requirements to protect private life and personal and family privacy. On the other hand, face-recognition cameras can assist law enforcement authorities in locating wanted persons and detecting (solving) crimes.

scholarly journals Facial Recognition System for People with and without Face Mask in Times of the COVID-19 Pandemic

2021 ◽  
Vol 13 (12) ◽  
pp. 6900
Author(s):  
Jonathan S. Talahua ◽  
Jorge Buele ◽  
P. Calvopiña ◽  
José Varela-Aldás
Keyword(s):  
Facial Recognition ◽  
Face Mask ◽  
Recognition System ◽  
Classification Model ◽  
World Health ◽  
The Face ◽  
Recognition Systems ◽  
Facial Recognition System ◽  
Health Organization ◽  
Face Detector

In the face of the COVID-19 pandemic, the World Health Organization (WHO) declared the use of a face mask as a mandatory biosafety measure. This has caused problems in current facial recognition systems, motivating the development of this research. This manuscript describes the development of a system for recognizing people, even when they are using a face mask, from photographs. A classification model based on the MobileNetV2 architecture and the OpenCv’s face detector is used. Thus, using these stages, it can be identified where the face is and it can be determined whether or not it is wearing a face mask. The FaceNet model is used as a feature extractor and a feedforward multilayer perceptron to perform facial recognition. For training the facial recognition models, a set of observations made up of 13,359 images is generated; 52.9% images with a face mask and 47.1% images without a face mask. The experimental results show that there is an accuracy of 99.65% in determining whether a person is wearing a mask or not. An accuracy of 99.52% is achieved in the facial recognition of 10 people with masks, while for facial recognition without masks, an accuracy of 99.96% is obtained.

Real Time Facial Recognition System

2020 ◽  
pp. 1721-1726
Author(s):  
Ashwini ◽  
Vijay Balaji ◽  
Srivarshini Srinivasan ◽  
Kavya Monisha
Keyword(s):  
Real Time ◽  
Facial Recognition ◽  
Recognition System ◽  
Facial Recognition System

scholarly journals Attendance Management System Using Face Recognition Method

2021 ◽  
Vol 2089 (1) ◽  
pp. 012078
Author(s):  
Syed Mansoora ◽  
Giribabu Sadineni ◽  
Shaik Heena Kauser
Keyword(s):  
Classroom Management ◽  
Facial Recognition ◽  
Recognition System ◽  
College Attendance ◽  
Advantages And Disadvantages ◽  
Haar Cascade ◽  
Triplet Loss ◽  
Facial Recognition System ◽  
Work First ◽  
Component Time

Abstract When it comes to classroom management, the attendance check is a critical component. Time-consuming, particularly when it comes to open meetings, is checking attendance by calling names or by handing around a sign-in sheet to make it easier to commit fraud. An implementation of a real-time attendance check is described in this article in great detail facial recognition system and its outcomes. The system must be able to identify a student’s face in order for it to work first snap a photograph of the pupil and save it in a database as a reference for future use. During the event, there were students may be identified by using the webcam, which captures photos of their faces auto-detects faces and selects students with names that are most likely to match, and lastly, depending on the facial recognition findings, an excel file will be updated to reflect attendance. To identify faces in webcam footage, the system uses a pre-trained Haar Cascade model. As a result, a 128-bit FaceNet has been generated by training it to minimise the triplet loss. The dimensions of the facial picture. When two facial pictures have similar encodings If the two facial pictures are from the same student or different. Use of the system as part of a class, and the outcomes have been extremely positive. There has been a poll done to find out more about There are both advantages and disadvantages to using a college attendance system.

scholarly journals Design of facial recognition system implemented in an unmanned aerial vehicle for citizen security in Latin America

2019 ◽  
Vol 27 ◽  
pp. 04002
Author(s):  
Diego Herrera ◽  
Hiroki Imamura
Keyword(s):  
Neural Network ◽  
Latin America ◽  
Deep Learning ◽  
Mobile Devices ◽  
Unmanned Aerial Vehicle ◽  
Facial Recognition ◽  
Recognition System ◽  
Criminal Records ◽  
Aerial Vehicle ◽  
Facial Recognition System

In the new technological era, facial recognition has become a central issue for a great number of engineers. Currently, there are a great number of techniques for facial recognition, but in this research, we focus on the use of deep learning. The problems with current facial recognition convection systems are that they are developed in non-mobile devices. This research intends to develop a Facial Recognition System implemented in an unmanned aerial vehicle of the quadcopter type. While it is true, there are quadcopters capable of detecting faces and/or shapes and following them, but most are for fun and entertainment. This research focuses on the facial recognition of people with criminal records, for which a neural network is trained. The Caffe framework is used for the training of a convolutional neural network. The system is developed on the NVIDIA Jetson TX2 motherboard. The design and construction of the quadcopter are done from scratch because we need the UAV for adapt to our requirements. This research aims to reduce violence and crime in Latin America.

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