scholarly journals Enhancement of Face Recognition using Deep Learning

2019 ◽  
Vol 9 (2) ◽  
pp. 5072-5075
Keyword(s):  
Deep Learning ◽  
Face Recognition ◽  
Feature Detection ◽  
Facial Recognition ◽  
Recognition System ◽  
Detection Capability ◽  
Comparative Result ◽  
Facial Recognition System

Our aim in this paper is to increase the accuracy of existing facial recognition system on a comparative smaller dataset as per the requirements of present day. Namely in sensitive regions. The methodology that has been adopted is by combining more than one algorithms. The feature detection capability of harr cascade along with Ada boost to fetch to Bilinear CNN so that on a comparative smaller dataset can produce comparative result as on bigger dataset.

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.

scholarly journals Design of Facial Recognition System Based on Visual Communication Effect

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Xuhui Fu
Keyword(s):  
Face Recognition ◽  
Face Detection ◽  
Visual Communication ◽  
Facial Recognition ◽  
Recognition System ◽  
Image Capture ◽  
Hardware System ◽  
Face Recognition System ◽  
The Face ◽  
Facial Recognition System

At present, facial recognition technology is a very cutting-edge science and technology, and it has now become a very hot research branch. In this research, first, the thesis first summarized the research status of facial recognition technology and related technologies based on visual communication and then used the OpenCV open source vision library based on the design of the system architecture and the installed system hardware conditions. The face detection program and the image matching program are realized, and the complete face recognition system based on OpenCV is realized. The experimental results show that the hardware system built by the software can realize the image capture and online recognition. The applied objects are testers. In general, the OpenCV-based face recognition system for testers can reliably, stably, and quickly realize face detection and recognition in this situation. Facial recognition works well.

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 Design of Intelligent Facial Recognition System using AI for Surveillance Application

2020 ◽  
pp. 346-356
Author(s):  
Syed Ibrahim ◽  
Syed Nahid Suleman ◽  
Manikanta Suthapalli ◽  
Abhishek Sharma ◽  
Shilpa K S
Keyword(s):  
Face Recognition ◽  
Face Detection ◽  
Facial Recognition ◽  
Recognition System ◽  
Security System ◽  
Software Module ◽  
High Security ◽  
Trained Staff ◽  
Facial Recognition System ◽  
Surveillance Application

Organizations presently continue to encounter significant security concerns; consequently, they require much particularly trained staff to achieve the coveted protection. This staff performs blunders that may affect the extent of security. A suggested solution to the matter mentioned above is a Face Recognition Security System, which can monitor and identify trespassers to blocked or high-security areas and assist in overcoming the margin of manual human oversight. This system is comprised of two halves: the hardware part and the software part. The hardware module incorporates a camera, while the software module includes software that uses face-detection and face-recognition algorithms. If a person infiltrates the confine in question, a set of snaps are captured by the camera and dispatched to the software to be examined/identified and equated with an existent database of trusted people. An alert is conveyed to the user if the infiltrator is not recognized.

scholarly journals An Separation of Different Facial Expression Recognition System

2019 ◽  
Vol 8 (6S4) ◽  
pp. 438-441
Keyword(s):  
Face Recognition ◽  
Facial Expressions ◽  
Facial Recognition ◽  
Recognition Rate ◽  
Recognition System ◽  
Digital Data ◽  
Expression Recognition ◽  
Share Data ◽  
The Face ◽  
Facial Recognition System

Face recognition is one of the hot topics in the current world and one of the popular topics of computer studies. Today face recognition in the network society and access to digital data is gaining more attention. The facial recognition system technology is a biometric assessment of a human's face. There are many facial recognition techniques that are intended depending on facial expressions extraction, one of which is 3D facial recognition, as well as their fusion,is difficult. During preprocessing measures for picture recognition to remove only expression-specific characteristics from the face and prevent their issues with a convolution neural network. We can also use some theorems such as LBP and Taylor's theorem to model face recognition. In particular, for cloud robots, we can also use this facial recognition on robots. The robot can perform functions and share data between servers and devices. Seven fundamental expressions are used to identify and classify: happiness, shock, fear, disgust, sadness, rage, and a neutral condition. Until now, the recognition rate is quite up to the expectation stage, but it still tries to enhance. To enhance the recognition frequency of facial image recognition, feelings are chosen by the vibrant Bayesian network technique to depict the development of facial awareness in addition to various emotional operations of facial expressions. The ICCA techniques involve various multivariate sets of distinct facial features that could be eyes, nose, and mouth.

scholarly journals INTEGRATION OF USER INTERFACE WITH FACIAL RECOGNITION SYSTEM

2020 ◽  
pp. 111-115
Author(s):  
D.Manasa ◽  
N.Ramya Sri ◽  
Sk.Naveed ◽  
N.Ramya
Keyword(s):  
Face Recognition ◽  
High Probability ◽  
Facial Recognition ◽  
Recognition System ◽  
Probability Of Error ◽  
Traditional System ◽  
The Face ◽  
Facial Recognition System ◽  
Python Programming ◽  
Recognition Technique

Attendance of students in a large classroom is hard to be handled by the traditional system, as it is time-consuming and has a high probability of error during the process of inputting data into the computer. This paper proposed automated attendance marking system using face recognition technique. The system will help to find the positive and negative of the face and Eigen face algorithm for face recognition by using python programming and OpenCV library. The proposed method using PCA to resolve the problems such as lightning of the images, and the direction of the student faces. The attendance of the student was updated to the Excel sheet after student's face has been recognized. KEYWORDS: PCA, Facial Recognition, ERP, Classroom, Attendance

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