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Salama, Ramiz, and Mohamed Nour. "Security Technologies Using Facial Recognition." Global Journal of Computer Sciences: Theory and Research 13, no. 1 (2023): 01–27. http://dx.doi.org/10.18844/gjcs.v13i1.8294.

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Abstract
 
 Faces are one of the simplest methods to determine a person's identity. Face recognition is a unique identifying method that uses an individual's traits to determine the identity of that individual. The proposed recognition process is divided into two stages: face recognition and object recognition. Unless the item is very close, this procedure is very rapid for humans. The recognition of human faces is introduced next. The stage is then reproduced and used as a model for facial image recognition (face recognition). That's one of the professionally created and well-resear
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P, Gangalakshmi. "Email Security using Facial Recognition." International Journal for Research in Applied Science and Engineering Technology 13, no. 4 (2025): 3861–68. https://doi.org/10.22214/ijraset.2025.69121.

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The project aims to bolster email security by employing advanced facial recognition technology. Leveraging OpenCV and convolutional neural networks (CNNs), the system verifies the identity of users attempting to access email accounts by analyzing facial biometrics. This approach enhances authentication measures, mitigates the risks of unauthorized access, and strengthens overall email privacy and confidentiality. Through real-time facial recognition algorithms, the system ensures secure access to email accounts, providing a robust defense against potential security breaches.
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Pinter, Robert, and Sanja Maravić Čisar. "Facial Recognition for Security Systems." Interdisciplinary Description of Complex Systems 22, no. 3 (2024): 341–54. https://doi.org/10.7906/indecs.22.3.9.

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Mundhe, Mr Kunal P. "ATM Security based on Face Verification." International Journal for Research in Applied Science and Engineering Technology 12, no. 3 (2024): 3171–76. http://dx.doi.org/10.22214/ijraset.2024.59589.

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Abstract: To provide a reliable security solution, this project focuses on creating an ATM security system based on facial recognition using OpenCV, machine learning, and deep learning. The paper examines how facial recognition technology can improve ATM security, offering a non-intrusive and highly accurate method of identity verification. By analyzing unique facial features, such as facial component sizes and shapes, this technology can authenticate users in real-time reliably. The proposed system integrates facial recognition software with existing ATM infrastructure. Users are prompted to
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Uzaifuddin Ahmeduddin,, Mohammed. "Facial Recognition-Based Home Security System." International Scientific Journal of Engineering and Management 04, no. 06 (2025): 1–9. https://doi.org/10.55041/isjem03956.

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ABSTRACT: Face detection has appeared as a vital component of modern security systems, with applications ranging from mobile authentication to surveillance. This research explores a face detection system designed using image processing techniques to enhance home security. The system captures live video, detects faces, and classifies them as either family members or unknown individuals. On identifying an unknown face, the system sends a mobile notification to the homeowner. This paper presents the methodology, implementation, and performance evaluation of the system, highlighting its potential
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Mehta, Munish. "Facial Recognition in Public Areas." Journal of Informatics Electrical and Electronics Engineering (JIEEE) 2, no. 2 (2021): 1–7. http://dx.doi.org/10.54060/jieee/002.02.013.

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The security of information nowadays is very significant and difficult, so there are a number of ways to improve security. Especially in public areas like airports, railway stations, Universities, ATMs, etc. and security cameras are presently common in these areas. So, in this paper, we are presenting how Facial recognition can be used in public areas like airports, toll gates, offices, etc. We are comparing or matching a face of a person who we want to detect, with the video which is recorded through CCTV. There are certain algorithms to detect faces from video like through HAAR cascades, eig
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K.U, Bhavishya, and Akshatha C H. "Facial Recognition in Smart Devices: Enhancing Security and Convenience." International Research Journal of Computer Science 12, no. 03 (2024): 102–8. https://doi.org/10.26562/irjcs.2025.v1203.02.

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Facial recognition technology (FRT) has become an essential component of modern security and convenience, integrating biometrics with advanced artificial intelligence (AI) techniques. This technology enables accurate identification and verification of individuals by analyzing facial characteristics, making it widely applicable in access control, security monitoring, and time attendance systems. The evolution of FRT dates back to the 1960s, progressing from manual facial measurements to deep learning-based algorithms utilizing convolutional neural networks (CNNs). Recent advancements, including
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Bein, Adrian Sean, and Alexander Williams. "Development of Deep Learning Algorithms for Improved Facial Recognition in Security Applications." IAIC Transactions on Sustainable Digital Innovation (ITSDI) 5, no. 1 (2023): 19–23. http://dx.doi.org/10.34306/itsdi.v5i1.605.

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This research aims to develop artificial intelligence (AI) algorithms in the context of facial recognition with a focus on increasing accuracy in difficult environmental conditions. Although facial recognition technology has made great progress, challenges such as poor lighting, variations in facial expressions, and head rotation are still problems that must be overcome. The research methodology involved collecting a wide dataset covering a wide variety of faces under various environmental conditions. This data is then processed and its features are extracted using computer image processing te
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Riyadani, Moh Eki, and Subiyanto Subiyanto. "Sistem Keamanan Untuk Otorisasi Pada Smart Home Menggunakan Pengenalan Wajah Dengan Library OpenCV." Jurnal SISKOM-KB (Sistem Komputer dan Kecerdasan Buatan) 5, no. 2 (2022): 69–77. http://dx.doi.org/10.47970/siskom-kb.v5i2.284.

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As industrial 4.0 advances such as Internet of Things (IoT), Big Data, Cloud Computing , and Artificial Intelligent (AI) has prompted reseachers to innovate in various fields, including security systems. The security system is an important issue due to rise of theft in a residence. A security system is needed for home authorizon to prevent the crime of theft. Security systems are built using facial recognition. The research proposes to develop a security system using facial recognition based Raspberry Pi with Python programming and utilize the OpenCV. System testing includes training function
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K, Mohd Amer. "Access Control Using Facial Recognition." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 08, no. 04 (2024): 1–5. http://dx.doi.org/10.55041/ijsrem30467.

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The field of smart home technology has grown by leaps and bounds over the last few decades. This development has made several new products available that can add convenience and security to facility. People became aware of smart home devices with the introduction of the smart thermostat, but these thermostats were only the beginning to smart homes. Smart devices helps people manage their sched-ules, grocery lists, home lighting and even the home security. These devices work together to make life a bit easier as well as safer. One group of such smart home security devices that are gaining popul
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Barthe, Dr Gilles Alonso,Marcos. "IMPROVING SECURITY AND OPERATIONAL EFFICIENCY: FACIAL RECOGNITION-BASED ACCESS CONTROL AT AL-IMAN WORKSHOP." International journal of networks and security 5, no. 3 (2025): 06–12. https://doi.org/10.55640/ijns-05-01-01.

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This study explores the implementation of a facial recognition-based access control system for the Al-Iman Workshop to enhance security and efficiency in managing access. The use of biometric systems, particularly facial recognition, has become a popular solution for secure access in various sectors. This paper assesses the design and effectiveness of integrating facial recognition technology in an industrial workshop setting, addressing concerns such as accuracy, security, and user privacy. Data was collected from the system’s performance, including its ability to identify workers, control ac
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Wang, Shengdi. "Facial recognition - A literature review." Applied and Computational Engineering 87, no. 1 (2024): 6–13. http://dx.doi.org/10.54254/2755-2721/87/20241560.

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This paper analyses the main technologies for face recognition, a critical biometric tool for identity verification and security across various sectors. A comprehensive overview of traditional and modern facial recognition technologies will be provided, examining their key features such as age, pose, and illumination. The study discusses the evolution and current state of facial recognition, highlighting significant advancements and applications in recent years. The objective is to offer a detailed understanding of how these technologies function and their implications for security and identit
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Rahmatunnisa, Elsa Nabila, Billy Adrian Fernanda, Yusuf Maulana, and Ali Maulana Hapid Aripin. "Implementasi Sistem Keamanan Rumah Berbasis Pengenalan Wajah untuk Peningkatan Keamanan Residensial." Infotek : Jurnal Informatika dan Teknologi 7, no. 1 (2024): 205–15. http://dx.doi.org/10.29408/jit.v7i1.23868.

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The objective of this research is to develop a home security system that utilizes facial recognition technology using the Haar Cascade method and ESP32CAM. In the face of criminal threats, the importance of an effective home security system is increasing. The facial recognition method employed in this study is the Haar Cascade method, which utilizes specific facial features to identify individual identities. The ESP32CAM sensor is used as a camera to capture facial images of the home occupants. The research involves the process of collecting facial image data from the home occupants, which is
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Tiwari, Er Shesh Mani, and Er Mohd Shah Alam. "Facial Emotion Recognition." International Journal for Research in Applied Science and Engineering Technology 11, no. 2 (2023): 490–94. http://dx.doi.org/10.22214/ijraset.2023.49067.

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Abstract: Facial Emotion Recognition plays a significant role in interacting with computers which help us in various fields like medical processes, to present content on the basis of human mood, security and other fields. It is challenging because of heterogeneity in human faces, lighting, orientation, poses and noises. This paper aims to improve the accuracy of facial expression recognition. There has been much research done on the fer2013 dataset using CNN (Convolution Neural Network) and their results are quite impressive. In this work we performed CNN on the fer2013 dataset by adding image
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Karale, Dr Ankita. "Online Transaction Security Using Face Recognition: A Review." International Journal for Research in Applied Science and Engineering Technology 10, no. 6 (2022): 2709–17. http://dx.doi.org/10.22214/ijraset.2022.44214.

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Abstract: The growing development of the e-commerce market is of great significance in the world. In this online shopping process, the security of personal information and debit card or credit card information increases the popularity of e-commerce and is an important part. This paper provides limited information and is necessary for transferring money by online transactions by securing data and trust of customers. Facial recognition technology identifies a person's information through a digital image. It is automatically determined. It is mainly used in security systems. It matches facial rec
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Wang, Chun-Fang, and Dong-Joo Kim. "How Facial Recognition Technology Impacts Resident Security." Journal of Contents and Industry 6, no. 4 (2024): 23–28. https://doi.org/10.55387/jci.2024.06.04.04.

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H, Dr Ravishankar, Vishal Yogish Rao, Nishant Rawat, and Sindhuja Chowdhary. "Biometric Access Control: Facial Recognition & QR Code Based Security System." International Journal of Research Publication and Reviews 6, no. 2 (2025): 3585–91. https://doi.org/10.55248/gengpi.6.0225.0959.

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Nigam, Harshit. "Review of Facial Recognition Techniques." International Journal for Research in Applied Science and Engineering Technology 10, no. 1 (2022): 1740–43. http://dx.doi.org/10.22214/ijraset.2022.40077.

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Abstract: Facial Recognition, the biggest breakthrough in Biometric identification and security since fingerprints, uses an individual’s facial features to identify and recognize them. A technology that seems too farfetched taken straight from a science fiction novel is now available in smartphones in the palm of our hands. Facial Recognition has gained traction as the primary method of identification whether its mobile phones, smart security systems, ID verification or something as simple as login in a website. Recent strides in facial recognition technologies have made it possible to design,
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Murdani, Hati, Elsa Listia Bella, and Agung Fatwanto. "Merancang sistem keamanan berbasis face recognition pada layanan sirkulasi perpustakaan." Daluang: Journal of Library and Information Science 4, no. 2 (2024): 82–96. https://doi.org/10.21580/daluang.v4i2.2024.21976.

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Purpose. This article aims to design a security system for library circulation services based on facial recognition, focusing specifically on collection lending services. The proposed system seeks to usher libraries into a new era where efficiency and security are prioritized, while also serving as an example of innovation in modern library circulation security systems.Methodology. The system design follows an object-oriented approach, employing the UML language with activity diagrams and use case diagrams to model the processes.Results and discussion. The proposed system includes a use case d
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Sumit, Sumit, and Nikhat Raza khan. "Security Implications of IoT-Enabled Mobile Net Facial Recognition System." Journal of Intelligent Systems and Internet of Things 13, no. 2 (2024): 231–44. http://dx.doi.org/10.54216/jisiot.130219.

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Face recognition technology is gaining popularity for security, access management, and user identification. A novel facial recognition method employing cutting-edge deep learning algorithms and attention processes reduces false positives in this study. This technique was designed to approach facial recognition differently. We demonstrate statistically substantial recognition gains over current approaches through extensive research and experimentation. The recommended solution uses an attention device and a complex feature extraction module. The pieces work together to highlight distinctive cha
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Santoso, Widi, Rahayu Safitri, and Samidi Samidi. "Integration of Artificial Intelligence in Facial Recognition Systems for Software Security." sinkron 8, no. 2 (2024): 1208–14. http://dx.doi.org/10.33395/sinkron.v8i2.13612.

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Facial recognition technology, a cornerstone in modern software security, has seen significant advancements through the integration of Artificial Intelligence (AI). This research focuses on enhancing facial recognition systems by incorporating sophisticated machine learning algorithms and deep neural networks. By doing so, the goal is to increase the accuracy and reliability of these systems in security applications. The study uses a variety of facial datasets to train AI models that are adept at extracting facial features and recognizing patterns. These models are subjected to rigorous testin
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Azar, Mitra. "Algorithmic Facial Image." A Peer-Reviewed Journal About 7, no. 1 (2018): 26–35. http://dx.doi.org/10.7146/aprja.v7i1.115062.

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 Facial tracking technologies have been incorporated in digital cameras for many years, and are offered to users of social networks such as Facebook to facilitate and automatize tagging (the process of recognizing one’s face in a picture and associating it with a user’s profile) and image sharing. Nevertheless, in recent times, facial recognition technologies seem to have taken a new turn, and from the simple recognition of faces with cameras and social networks they have become embedded in mainstream security technologies as much as in entertaining ‘face swap’ apps, transf
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Wang, Xiao, and Yan Li. "Facial Recognition System Based on Genetic Algorithm Improved ROI-KNN Convolutional Neural Network." Applied Bionics and Biomechanics 2022 (October 10, 2022): 1–11. http://dx.doi.org/10.1155/2022/7976856.

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The facial recognition system is an application tool that uses artificial intelligence technology and biometrics technology to analyze and recognize the facial feature information of the human face. It is widely used in various fields, such as attendance and access control management in schools and companies, identity monitoring in stations and stores, facial recognition for fugitive criminals, and facial payment on mobile terminals. However, due to the short development time of the facial recognition system, the facial recognition system has the problem of low recognition accuracy when the re
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Sd, Vaheeda. "Facial Recognition and Shock Protection: A Comprehensive Anti-Theft System for Vehicles." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 08, no. 04 (2024): 1–5. http://dx.doi.org/10.55041/ijsrem30814.

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Vehicle Anti-Theft Detection and Protection with Shock employs a robust security system integrating facial recognition technology and shock protection mechanisms. A camera, connected to a Python-installed PC, facilitates facial recognition to identify authorized users. In the event of an unrecognized face, the system triggers an immediate response by sending an alert email to the registered user. This aspect adds an extra layer of security to deter potential thefts. In addition to the facial recognition feature, the project incorporates a shock protection mechanism inspired by a mosquito bat.
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K, Sneha, Manoj V, Darshan Gowda M S, Girish S, Harsha C, and Giri Gowrav R. "Advancements in Face Recognition through Machine Learning Techniques." Journal of Data Engineering and Knowledge Discovery 1, no. 1 (2024): 26–31. http://dx.doi.org/10.46610/jodekd.2024.v01i01.004.

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The majority of disciplines in the modern world rely heavily on face recognition. The identification of fraud and security is one of the most popular disciplines. The process of positioning the facial landmarks on the face to provide precise points for facial recognition is known as facial alignment. Identification and face detection are crucial for detecting fraud. Consequently, the identification of profile and semi-profile facial features is essential for security reasons. The facial-aligned dataset can be used to get the Hourglass model's face alignment, which improves face recognition acc
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Mubashshir, Mr, Kshitij Shinghal, and Manas Singhal. "Review on Facial Recognition." International Journal on Recent and Innovation Trends in Computing and Communication 7, no. 8 (2019): 07–12. http://dx.doi.org/10.17762/ijritcc.v7i8.5345.

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Generally face recognition perform many operations in our daily life such as security purpose identification of people and verification purpose. The basic aim of my project is to design an effective and secure technique for authentication using face recognition that can search or recognize a human face among the thousands of persons and improve the performance of face recognition system in low light conditions and also evaluate the performance of the designed framework by comparing the performance of existing face recognition system. This study also provides a automatic system through which a
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Naresh Choudary, M., Seelam Srujan, Veeramalla Aswini Laya, Neelapu Neeraj Reddy, and Ranga Shivani. "FACE RECOGNITION BASED STUDENT ATTENDANCE USING PYTHON AND OPENCV." YMER Digital 21, no. 04 (2022): 481–88. http://dx.doi.org/10.37896/ymer21.04/47.

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Face recognition is one of the important applications of image processing, where we can scan the face of an individual using Open source Computer Vision library (OpenCV). Introducing this software had proliferated the digital market in security and safety. These days Facial recognition is used around the globe for multiple purposes like tracking & security. And it's not just for security and safety; facial recognition software is now being used in transportation, the hotel industry, and online banking. As it’s actively working in different domains according to their needs, our main goal is
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Naresh Choudary, M., Seelam Srujan, Veeramalla Aswini Laya, Neelapu Neeraj Reddy, and Ranga Shivani. "FACE RECOGNITION BASED STUDENT ATTENDANCE USING PYTHON AND OPENCV." YMER Digital 21, no. 04 (2022): 481–88. http://dx.doi.org/10.37896/ymer21.04/47.

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Face recognition is one of the important applications of image processing, where we can scan the face of an individual using Open source Computer Vision library (OpenCV). Introducing this software had proliferated the digital market in security and safety. These days Facial recognition is used around the globe for multiple purposes like tracking & security. And it's not just for security and safety; facial recognition software is now being used in transportation, the hotel industry, and online banking. As it’s actively working in different domains according to their needs, our main goal is
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Ghani, Muhammad Ahmad Nawaz Ul, Kun She, Muhammad Arslan Rauf, et al. "Toward robust and privacy-enhanced facial recognition: A decentralized blockchain-based approach with GANs and deep learning." Mathematical Biosciences and Engineering 21, no. 3 (2024): 4165–86. http://dx.doi.org/10.3934/mbe.2024184.

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<abstract><p>In recent years, the extensive use of facial recognition technology has raised concerns about data privacy and security for various applications, such as improving security and streamlining attendance systems and smartphone access. In this study, a blockchain-based decentralized facial recognition system (DFRS) that has been designed to overcome the complexities of technology. The DFRS takes a trailblazing approach, focusing on finding a critical balance between the benefits of facial recognition and the protection of individuals' private rights in an era of increasing
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Kundu, Subhasis. "Transforming Identity Verification: Cutting-Edge Face Recognition with AI-Powered Computer Vision." International Scientific Journal of Engineering and Management 01, no. 01 (2022): 1–7. https://doi.org/10.55041/isjem00188.

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This study explored the transformative effects of AI-driven facial recognition technology on identity verification systems. It delves into the recent progress in computer vision and deep learning algorithms, which have greatly improved the accuracy and speed of facial recognition. This study highlights the potential uses of this technology in various fields such as security, finance, and personalized services. It also examines the ethical issues and privacy concerns arising from the widespread adoption of facial recognition. Furthermore, this study addresses the challenges of creating robust s
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Yamin, Iqra, Yang Gaoming, Marcel BAKALA, Muhammad Asad Yamin, and Usama Masood. "Security-oriented Face Detection Technology Utilizing Deep Learning Techniques Along with the CASIA Datasets." International Journal of Recent Technology and Engineering (IJRTE) 12, no. 5 (2024): 1–11. http://dx.doi.org/10.35940/ijrte.e7970.12050124.

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Recently, face recognition technology has become increasingly important for safety purposes. Masks are now required in most countries and are increasingly used. Public health professionals advise people to conceal their facial features outdoors to reduce COVID-19 transmission by 65%. Detecting people without masks on their faces is crucial. This has become widely used as face recognition outperforms PINs, passwords, fingerprints, and other safety verification methods. Sunglasses, scarves, caps, and makeup have made facial identification harder in recent decades. Thus, such masks impact facial
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Iqra, Yamin. "Security-oriented Face Detection Technology Utilizing Deep Learning Techniques Along with the CASIA Datasets." International Journal of Recent Technology and Engineering (IJRTE) 12, no. 5 (2024): 1–11. https://doi.org/10.35940/ijrte.E7970.12050124.

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<strong>Abstract:</strong> Recently, face recognition technology has become increasingly important for safety purposes. Masks are now required in most countries and are increasingly used. Public health professionals advise people to conceal their facial features outdoors to reduce COVID-19 transmission by 65%. Detecting people without masks on their faces is crucial. This has become widely used as face recognition outperforms PINs, passwords, fingerprints, and other safety verification methods. Sunglasses, scarves, caps, and makeup have made facial identification harder in recent decades. Thus
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priscilla, Pramila. "Enhancing ATM Functionality with a Single Card Solution for Multiple Bank Accounts." INTERNATIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 06 (2025): 1–9. https://doi.org/10.55041/ijsrem49390.

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ABSTRACT This project seeks to modernize traditional magnetic strip ATM cards by transitioning to RFID-based cards, each possessing a unique identifier. The data processing component is managed by an Arduino Mega microcontroller, which interfaces with various sensors to facilitate financial transactions. User authentication is accomplished through a fingerprint module for biometric verification, augmented by the implementation of a One-Time Password (OTP) transmitted to the registered mobile phone to enhance security. The system is designed to allow users to link multiple bank accounts to thei
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Choudhury, Ziaul Haque, and M. Munir Ahamed Rabbani. "Cosmetic applied based face recognition for biometric passport." International Journal of Intelligent Unmanned Systems 8, no. 1 (2019): 3–22. http://dx.doi.org/10.1108/ijius-02-2019-0016.

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Purpose Nowadays, the use of forged e-passport is increasing, which is threatening national security. It is important to improve the national security against international crime or terrorism. There is a weak verification process caused by lack of identification processes such as a physical check, biometric check and electronic check. The e-passport can prevent the passport cloning or forging resulting from the illegal immigration. The paper aims to discuss these issues. Design/methodology/approach This paper focuses on face recognition to improve the biometric authentication for an e-passport
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Dive, Bhushan. "Advanced Vehicle Locking System Using Facial Recognition." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 08, no. 04 (2024): 1–5. http://dx.doi.org/10.55041/ijsrem31151.

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Access control systems are crucial for vehicle security. This study presents an innovative method employing a Raspberry Pi-based system integrated with face-api.js, along with dlib libraries, to establish a secure vehicle access control system. Facial recognition algorithms are utilized for user authentication, adding an extra level of security. Any unauthorized access prompts an alert to the administrator, improving real-time monitoring and response capabilities.
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Mrak, M. "FACE RECOGNITION METHODS IN VIDEO SURVEILLANCE SYSTEMS USING MACHINE LEARNING." Information and communication technologies, electronic engineering 3, no. 2 (2023): 33–42. http://dx.doi.org/10.23939/ictee2023.02.033.

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The article is dedicated to the investigation of face identification methods and aims to determine the most suitable one for a security system based on facial recognition from surveillance cameras. The time costs of these methods and their robustness against geometric scale distortions and rotations in various planes have been analyzed. Custom datasets have been generated for experimentation purposes. Special attention has been given to striking a balance between the speed and accuracy of the examined methods for their utilization as the initial stage of a security system based on facial recog
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NASCIMENTO PINHEIRO VARGAS, ÉRICA, and MÔNICA MATOS RIBEIRO. "Reconhecimento facial como política de segurança pública no estado da Bahia." Revista Crítica de Sociologia e Política 22, no. 3 (2023): 190–216. http://dx.doi.org/10.59901/2318-373x/v22n3a7.

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The objective of this article was to describe the main benefits and risks of implementing the public policy of facial recognition, via artificial intelligence, applied by the Secretariat of Public Security in the State of Bahia through Vídeo Policiamento – Mais Inteligência na Segurança and Vídeo-Polícia Expansão projects. The study was based on the assumption of the need for more accuracy in the application of facial recognition, via artificial intelligence, for use as a public security policy, in order to avoid possible violations of fundamental rights of freedom, privacy and protection of p
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Amutha, Dr R. "AI Based Office Monitoring System using Python." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 01 (2025): 1–9. https://doi.org/10.55041/ijsrem41233.

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In today’s office environment, organizations face the challenge of effectively monitoring employee performance and ensuring workplace security. Companies need reliable systems to track employee attendance and at the same time they need to monitor employees and also ensure that employees remain productive, focused, and engaged during work hours. However, current or existing monitoring systems often focus on one aspect either security or performance without integrating both in the modern workplace. This paper discusses about the methodologies for facial attendance based on facial recognition, po
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Maulana, Abi, Aulia Ullah, Ahmad Faizal, and Hilman Zarory. "Dual Sistem Keamanan Pada Pintu Dengan Pengenalan Wajah Local Binary Pattern Histogram (LBPH) Dan Sidik Jari serta Notifikasi Telegram." JURNAL Al-AZHAR INDONESIA SERI SAINS DAN TEKNOLOGI 10, no. 2 (2025): 153. https://doi.org/10.36722/sst.v10i2.3696.

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&lt;p&gt;&lt;strong&gt;Conventional door security systems, such as padlocks and manual keys, have weaknesses, including vulnerability to duplication and the risk of loss. Biometric-based systems, such as facial recognition, offer a more reliable solution through unique user identification. This study develops a door security system using the Local Binary Pattern Histogram (LBPH) method for facial recognition, complemented by fingerprint verification as an additional security layer and real-time notifications via the Telegram application. The LBPH method was chosen for its ease of implementatio
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PAWAR, RAVI, and DR RAVI SHANKAR SHARMA. "Facial Recognition Using Video Streaming." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 08, no. 11 (2024): 1–7. http://dx.doi.org/10.55041/ijsrem39128.

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Facial recognition has become an essential technology in numerous applications, including security, surveillance, and human-computer interaction. With the advent of real-time video streaming, facial recognition systems are now tasked with handling the continuous flow of visual data. This paper explores the integration of facial recognition algorithms into video streaming systems, investigating the challenges, methodologies, and applications of real-time face detection and identification. We present a framework for implementing facial recognition in live video streams, assess the performance of
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Adetunji, Temitope Oluwafunmilayo. "ADVANCEMENTS IN AI-POWERED FACIAL RECOGNITION FOR SECURE USER AUTHENTICATION IN E-LEARNING ENVIRONMENTS." Journal of Technology & Innovation 4, no. 2 (2024): 63–65. https://doi.org/10.26480/jtin.02.2024.63.65.

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Strong security protocols are essential to guarantee user authentication and data integrity amidst the rapidgrowth of e-learning platforms. Artificial Intelligence (AI)-based facial recognition has grow into a widely used technology in the modern world with anextensive range of applications. Using machine learning and algorithmic methodologies, the technology analyzes and recognizes faces in digital photos or videos. In this review paper we explores recent developments in artificial intelligence (AI)-assisted facial recognition technologies designed to enhance user authentication and security
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Jain, Ayush. "Secure Authentication for Banking Using Face Recognition." Journal of Informatics Electrical and Electronics Engineering (JIEEE) 2, no. 2 (2021): 1–8. http://dx.doi.org/10.54060/jieee/002.02.001.

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With the increasing demand for online banking lack of security in the system has been felt due to a tremendous increase in fraudulent activities. Facial recognition is one of the numerous ways that banks can increase security and accessibility. This paper proposes to inspect the use of facial recognition for login and for banking purposes. The potency of our system is that it provides strong security, username and password verification, face recognition and pin for a successful transaction. Multilevel Security of this system will reduce problems of cyber-crime and maintain the safety of the in
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Pushilal, Arnab, Sulakshana Chakraborty, Raunak Singhania, and P. Mahalakshmi. "Implementation of Facial Recognition for Home Security Systems." International Journal of Engineering & Technology 7, no. 4.10 (2018): 55. http://dx.doi.org/10.14419/ijet.v7i4.10.20706.

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In this paper, the design and development of a home security system has been detailed which uses facial recognition to conform the identity of the visitor and taking various security measures when an unauthorized personnel tries accessing the door. It demonstrates the implementation of one of the most popular algorithm for face recognition i.e. principal component analysis for the purpose of security door access. Since PCA converts the images into a lower dimension without losing on the important features, a huge set of training data can be taken. If the face is recognized as known then the do
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Dr. S. Gandhimathi and Ms. J. Soundarya. "Credit Card Transaction Security Using Facial Recognition Technology." International Journal of Scientific Research in Computer Science, Engineering and Information Technology 11, no. 2 (2025): 2358–65. https://doi.org/10.32628/cseit23112573.

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The most prevalent issue nowadays in the modern world is credit card fraud. This is due to the growth in internet transactions and e-commerce websites. When a credit card is stolen and used for unauthorized purposes, or when a fraudster uses the card's information for his own gain, credit card fraud happens. Because the credit card offers significant usage as a payment instrument, it is often used. As we all know, there are several opportunities for attackers or hackers to acquire sensitive data from online transactions. For both valid and invalid transactions, the information is processed and
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Singh, Akash, Jay Nikhal, Rahul Khandekar, Supriya Gode, and Deepa Athawle. "Facial Recognition & Authentication in E-Learning Portal." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 04 (2025): 1–9. https://doi.org/10.55041/ijsrem43915.

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With the rapid growth of online education, ensuring secure and reliable authentication methods has become a critical concern. Traditional login mechanisms, such as passwords and PINs, are vulnerable to breaches, unauthorized access, and identity fraud. This paper explores the implementation of facial recognition technology as a secure and efficient authentication system for e-learning portals. Facial recognition leverages biometric features to verify users' identities, offering a seamless and user-friendly experience while enhancing security. The proposed system integrates artificial intellige
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Frenza, Devira, and Riki Mukhaiyar. "Aplikasi Pengenalan Wajah dengan Metode Adaptive Resonance Theory (ART)." Ranah Research : Journal of Multidisciplinary Research and Development 3, no. 3 (2021): 147–53. http://dx.doi.org/10.38035/rrj.v3i3.392.

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Image processing technology (image processing) at this time can be done using a computer. An image that can be recognized by a computer is called a digital image. One application of image processing (image processing) is the field of face detection (face detection). Today's face detection system is one of the most important technologies. Because, facial recognition systems are closely related to security systems, where facial recognition systems can be applied in various places and situations, namely: security system applications, facial disguise recognition applications, and database informat
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Pulugu, Dileep, Anusha P, Ratan Rajan Srivastava, Kalaivani R, and Subharun Pal. "MACHINE LEARNING-BASED FACIAL RECOGNITION FOR VIDEO SURVEILLANCE SYSTEMS." ICTACT Journal on Image and Video Processing 14, no. 2 (2023): 3149–54. http://dx.doi.org/10.21917/ijivp.2023.0448.

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Video surveillance systems play a crucial role in ensuring public safety and security. However, the traditional methods of surveillance often fall short in effectively identifying individuals, particularly in crowded or dynamic environments. This research addresses the limitations of conventional video surveillance by proposing a machine learning-based facial recognition system. The increasing demand for robust security measures necessitates the development of advanced technologies in video surveillance. Facial recognition has emerged as a promising solution, but existing systems struggle with
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Lee, Cheol-Ho. "Face Recognition Technology and Privacy." Korean Society of Private Security 23, no. 1 (2024): 89–114. http://dx.doi.org/10.56603/jksps.2024.23.1.89.

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Face recognition technology is a method that utilizes thermal infrared photography, three-dimensional measurement, and skeletal analysis to scan, store, and recognize facial shapes or thermal images. It verifies identity by comparing facial images captured by cameras with those in a stored photo database. This technology is extensively applied in various sectors, such as identity verification and access control, due to its high accuracy and quick identification capabilities. The advancement of facial recognition technology, coupled with CCTV, the Internet of Things (IoT), and widespread networ
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Zhang, Aodi, and Shibao Sun. "A Face Recognition Method Based on Transfer Learning and Attention Mechanism." International Journal of Computer Science and Information Technology 2, no. 2 (2024): 21–35. https://doi.org/10.62051/ijcsit.v2n2.02.

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With the popularization of network technology and the development of informatization, the security of personal identity information is receiving increasing attention. In fields such as finance, healthcare, and security, security requirements are increasing, and more reliable and secure identity verification methods are needed to protect personal information from illegal acquisition and use. Traditional identity verification methods, such as passwords and PIN codes, face problems such as being guessed, forgotten, and stolen. Based on the understanding of the limitations and shortcomings of trad
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Reshma, M. S*1 &. Sabeena M. 2. "A SURVEY ON FACIAL IMAGE RECOGNITION AND RECONSTRUCTION." INTERNATIONAL JOURNAL OF ENGINEERING SCIENCES & RESEARCH TECHNOLOGY AICT 2019 (April 4, 2019): 39–44. https://doi.org/10.5281/zenodo.2629254.

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Human face is essential information for robust applications. Facial Image Recognition and Reconstruction is always challenging in computer vision. The facial images are often present in very low resolution due to environmental influence and imaging equipment limitation. This can be solved by using many face super resolution techniques. Facial image recognition methods can be vision oriented or recognition oriented methods. Many works have been done in the progress of automatic Facial image Recognition and Reconstruction. This has many applications in security, health and human computer interac
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