Gotowe bibliografie tematyczne / Facial recognition security

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Gotowa bibliografia na temat „Facial recognition security”

Autor: Grafiati

Data publikacji: 2 czerwca 2025

Data aktualizacji: 31 lipca 2025

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Artykuły w czasopismach na temat "Facial recognition security"

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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Rozprawy doktorskie na temat "Facial recognition security"

Brien, Renaud. "Security, Privacy and Performance Improvements for Fuzzy Extractors." Thesis, Université d'Ottawa / University of Ottawa, 2020. http://hdl.handle.net/10393/40606.

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With the usage of biometrics becoming commonly used in a variety of applications, keeping those biometrics private and secure is an important issue. Indeed, the convenience of using biometrics for authentication is counteracted by the fact that they cannot easily be modified or changed. This can have dire consequences to a person if their biometrics are leaked. In the past decades, various techniques have been proposed to solve this problem. Such techniques range from using and storing randomized templates, using homomorphic encryption, or using biometric encryption techniques such as fu

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Cruz, Victor F. "Utilizing current commercial-off-the-shelf facial-recognition and public live video streaming to enhance national security." Thesis, Monterey, California: Naval Postgraduate School, 2014. http://hdl.handle.net/10945/43898.

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Approved for public release; distribution is unlimited<br>The nation’s security depends in part on proactive approaches and methods to evolving technologies for identifying persons of interest, enemies of state (foreign and domestic), potential acts of terrorism, and foreign intelligence. Currently, state and federal entities operate passive surveillance technologies with biometrics to identify and curtail national security threats, so as to act within the confines of the Act for Uniting and Strengthening America by Providing Appropriate Tools Required to Intercept and Obstruct Terrorism. Howe

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Ketab, Salam. "E-invigilation of e-assessments." Thesis, University of Plymouth, 2017. http://hdl.handle.net/10026.1/10144.

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E-learning and particularly distance-based learning is becoming an increasingly important mechanism for education. A leading Virtual Learning Environment (VLE) reports a user base of 70 million students and 1.2 million teachers across 7.5 million courses. Whilst e-learning has introduced flexibility and remote/distance-based learning, there are still aspects of course delivery that rely upon traditional approaches. The most significant of these is examinations. The lack of being able to provide invigilation in a remote-mode has restricted the types of assessments, with exams or in-class test a

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Alvarez, Rivera Luiggi Andre, and Huaman Bryan Eduardo Orellana. "Solución tecnológica para optimizar el proceso de identificación de delincuentes en Lima Metropolitana." Bachelor's thesis, Universidad Peruana de Ciencias Aplicadas (UPC), 2021. http://hdl.handle.net/10757/655226.

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En la actualidad, el incremento de actos delictivos se ha hecho más frecuente en Lima, por lo que es considerado como uno de los mayores problemas que afecta a nuestra sociedad. Esto se ve reflejado en los últimos reportes de seguridad ciudadana donde Lima es considerada una de las ciudades más peligrosas de América Latina. A su vez, las autoridades no cuentan con las herramientas suficientes para combatir a la delincuencia generando que la población se sienta insegura de caminar por las calles y aumentando la cantidad de actos delictivos. Esto incluye la escasez de tecnología que permita opti

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Filio, Torres Edgar Alfredo. "Diseño de un sistema de seguridad física mediante Reconocimiento Facial a través del flujo de video, siguiendo las mejores prácticas de las normas ISO 80601, 13154, 19794 y el NISTIR 8238, para el área de seguridad de una empresa minera." Bachelor's thesis, Universidad Peruana de Ciencias Aplicadas (UPC), 2021. http://hdl.handle.net/10757/656270.

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El presente trabajo se basa en el diseño de un sistema de seguridad física, aplicando tecnología de reconocimiento facial, para el control de acceso en una empresa del sector minero, este sistema permite tener un control robusto y confiable de los usuarios que ingresan y transitan por el campamento minero, este sistema se adapta a la nueva realidad que estamos viviendo, donde el distanciamiento social, el contacto físico personal y la medición de la temperatura, es un requisito indispensable. El diseño propuesto toma como referencia las mejores prácticas de las normas IEC 80601-2-59:2017 e ISO

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Norris-Jones, Lynne. "Demonstrate and document : the development of a best practice model for biometric access control management." Thesis, Cardiff Metropolitan University, 2011. http://hdl.handle.net/10369/6411.

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This thesis investigates the social, legal and ethical perceptions of participants towards the implementation of biometric access control systems within a sample of United Kingdom work-based environments. It focuses on the application of fingerprint scanning and facial recognition systems, whilst alluding to the development of more advanced (bleeding edge) technologies in the future. The conceptual framework is based on a tripartite model in which Maslow's Hierarchy of Needs is applied to the workforce whilst the principles of Utilitarianism and the Psychological Contract are applied to both m

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(8782193), Tyler Stephen Phillips. "Privacy-Preserving Facial Recognition Using Biometric-Capsules." Thesis, 2020.

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<div>In recent years, developers have used the proliferation of biometric sensors in smart devices, along with recent advances in deep learning, to implement an array of biometrics-based recognition systems. Though these systems demonstrate remarkable performance and have seen wide acceptance, they present unique and pressing security and privacy concerns. One proposed method which addresses these concerns is the elegant, fusion-based Biometric-Capsule (BC) scheme. The BC scheme is provably secure, privacy-preserving, cancellable and interoperable in its secure feature fusion design. </div><di

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Tremoço, João Francisco Gomes. "Improving deep learning face recognition for ID and travel document applications with quality assessment." Master's thesis, 2021. http://hdl.handle.net/10316/97961.

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Dissertação de Mestrado Integrado em Engenharia Física apresentada à Faculdade de Ciências e Tecnologia<br>Os métodos atuais de reconhecimento facial são baseados em redes neuronais que requerem grandes quantidades de dados para serem eficazes. Os grandes conjuntos de dados disponíveis publicamente são, em sua maioria, coleções de imagens de celebridades sem restrições. Estes conjuntos de dados não são otimizados para aplicações relacionadas com a segurança de documentos. Além disso, devido a questões de privacidade, os conjuntos de dados de imagens faciais úteis para o uso em situações que en

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Książki na temat "Facial recognition security"

W, Vorder Bruegge Richard, ed. Computer-aided forensic facial comparison. Taylor & Francis Group, 2010.

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Evison, Martin Paul, and Richard W. Vorder Bruegge. Computer-Aided Forensic Facial Comparison. Taylor & Francis Group, 2010.

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Evison, Martin Paul, and Richard W. Vorder Bruegge. Computer-Aided Forensic Facial Comparison. Taylor & Francis Group, 2010.

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Our biometric future: Facial recognition technology and the culture of surveillance. New York University Press, 2011.

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Clement, John G., and Murray K. Marks. Computer-Graphic Facial Reconstruction. Elsevier Science & Technology Books, 2005.

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Clement, John G., and Murray K. Marks. Computer-Graphic Facial Reconstruction. Academic Press, 2005.

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Shah, Rajiv, and Brendan Mcquade. Surveillance, Security, and Intelligence-Led Policing in Chicago. Edited by Larry Bennett, Roberta Garner, and Euan Hague. University of Illinois Press, 2017. http://dx.doi.org/10.5406/illinois/9780252040597.003.0012.

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This chapter summarizes the Chicago Police Department’s adoption of Intelligence-Led Policing (ILP) since the early-2000s as a crime prevention and deterrence strategy. It reviews the use of technology such as police observation devices (cameras), the centralization of the Police Department’s data operations at the Crime Prevention and Information Center, a sophisticated data analytics “fusion center,” and examines changing technologies of surveillance used by the police. The authors discuss the integration of police surveillance with privately-owned and operated camera systems, and explore ho

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Bindemann, Markus, ed. Forensic Face Matching. Oxford University Press, 2021. http://dx.doi.org/10.1093/oso/9780198837749.001.0001.

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Person identification at passport control, at borders, in police investigations, and in criminal trials relies critically on the identity verification of people via image-to-image or person-to-image comparison. While this task is known as ‘facial image comparison’ in forensic settings, it has been studied as ‘unfamiliar face matching’ in cognitive science. This book brings together expertise from practitioners, and academics in psychology and law, to draw together what is currently known about these tasks. It explains the problem of identity impostors and how within-person variability and betw

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Donald R, Rothwell, Elferink Alex G Oude, Scott Karen N, and Stephens Tim, eds. The Oxford Handbook of the Law of the Sea. Oxford University Press, 2015. http://dx.doi.org/10.1093/law/9780198715481.001.0001.

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Human activities have taken place in the world's oceans and seas for most of human history. With such a vast number of ways in which the oceans can be used for trade, exploited for natural resources and fishing, as well as concerns over maritime security, the legal systems regulating the rights and responsibilities of nations in their use of the world's oceans have long been a crucial part of international law. The United Nations Convention on the Law of the Sea comprehensively defined the parameters of the law of the sea in 1982, and since the Convention was concluded it has seen considerable

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Części książek na temat "Facial recognition security"

Smith, Marcus, Monique Mann, and Gregor Urbas. "Facial recognition." In Biometrics, Crime and Security. Routledge, 2018. http://dx.doi.org/10.4324/9781315182056-4.

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Lin, Yuchen, Zhehen Zheng, and Yang Zhou. "Facial Recognition." In Information Technology Security and Risk Management. CRC Press, 2024. http://dx.doi.org/10.1201/9781003264415-30.

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Dixit, Vibhu, Srishti Agarwal, and Nidhi Tyagi. "Home Security Using Facial Recognition System." In Proceedings of International Conference on Recent Trends in Computing. Springer Singapore, 2022. http://dx.doi.org/10.1007/978-981-16-7118-0_29.

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Ngo, Tan Quan, and Seokhoon Yoon. "Facial Expression Recognition on Static Images." In Future Data and Security Engineering. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-35653-8_42.

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Ujjwal, M. K., Sunil Parameswaran, V. Guna Chowdary, Varun Bharadwaj, and Dayananda Pruthviraja. "Comparative Analysis of Facial Expression Recognition Algorithms." In Data Science and Security. Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-97-0975-5_38.

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Majeed, Asim, and Said Baadel. "Facial Recognition Cane for the Visually Impaired." In Global Security, Safety and Sustainability - The Security Challenges of the Connected World. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-51064-4_32.

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Verma, Rajesh Kumar, Praveen Singh, Chhabi Rani Panigrahi, and Bibudhendu Pati. "ISS: Intelligent Security System Using Facial Recognition." In Advances in Intelligent Systems and Computing. Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-6584-7_10.

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Puvaneswari, G., M. Ramya, R. Kalaivani, and S. Bavithra Ganesh. "Smart Home Security System Using Facial Recognition." In Proceedings of Third International Conference on Sustainable Expert Systems. Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-19-7874-6_18.

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Shukla, Pratyush, and Mahesh Kumar. "Demystifying Facial Expression Recognition Using Residual Networks." In Cryptology and Network Security with Machine Learning. Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-2229-1_25.

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Liu, Liyuan, Lifeng Zhang, and Shixiang Jia. "Attention Bilinear Pooling for Fine-Grained Facial Expression Recognition." In Cyberspace Safety and Security. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-37352-8_47.

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Streszczenia konferencji na temat "Facial recognition security"

Venkatesan, C., Sathish K, Bolla Naganwesh, D. Shaheen, Rishant Kumar Sinha, and Musharraf Reza. "Facial Recognition Robots for Enhanced Safety and Smart Security." In 2024 Third International Conference on Smart Technologies and Systems for Next Generation Computing (ICSTSN). IEEE, 2024. http://dx.doi.org/10.1109/icstsn61422.2024.10670929.

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G, Balaraju, Kumar B. I. D, Gireesh Babu C. N, Ravi B. K, Chandrashekhara K. T, and Amoolya P. Shanbhag. "Vehicle Security by Facial Recognition Using Convolutional Neural Networks." In 2024 International Conference on Intelligent Computing and Emerging Communication Technologies (ICEC). IEEE, 2024. https://doi.org/10.1109/icec59683.2024.10837455.

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Patwal, Heera, Ramesh Kumar, Isarar Ahamad, Amit Mittal, Hemant Singh, and Shweta Goyal. "Facial Recognition in Cloud Security: Research Perspectives on Authentication Solutions." In 2024 4th International Conference on Advance Computing and Innovative Technologies in Engineering (ICACITE). IEEE, 2024. http://dx.doi.org/10.1109/icacite60783.2024.10617403.

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Kumar, Deepak, M. Kumaresan, and Shashikant Deepak. "Real-Time Facial Recognition in Computer Vision for Industrial Security." In 2024 International Conference on Advances in Computing Research on Science Engineering and Technology (ACROSET). IEEE, 2024. http://dx.doi.org/10.1109/acroset62108.2024.10743887.

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Kaushik, Priyanka, Harsh Kumar, Nancy Tyagi, Shubhang, Jatin, and Mrinal. "Improving Home Security through Facial Recognition in a Smart Environment." In 2024 International Conference on Smart Devices (ICSD). IEEE, 2024. http://dx.doi.org/10.1109/icsd60021.2024.10751272.

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Rajababu, Durgam, Madhu Chavva, T. N. Srinivas Rao, A. Aldo Tenis, D. Lavanya, and B. T. Geetha. "Deep Learning-Driven Real-Time Facial Recognition for Enhanced Security." In 2024 Asian Conference on Intelligent Technologies (ACOIT). IEEE, 2024. https://doi.org/10.1109/acoit62457.2024.10939332.

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Kadu, Anil, Samarveer Moray, Aditya Sakhare, Prathamesh Salokhe, Ameya Salunkhe, and Abhinav Salve. "Smart Door Security System with Facial Recognition: Design and Implementation." In 2024 International Conference on Progressive Innovations in Intelligent Systems and Data Science (ICPIDS). IEEE, 2024. https://doi.org/10.1109/icpids65698.2024.00060.

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Changala, Ravindra, K. RaviKiran Yasaswi, Mansoor Farooq, Shamim Ahmad Khan, Ajmeera Kiran, and S. Muthuperumal. "Advanced Facial Recognition with Behavioural Analysis for Intelligent Security Monitoring." In 2025 Fifth International Conference on Advances in Electrical, Computing, Communication and Sustainable Technologies (ICAECT). IEEE, 2025. https://doi.org/10.1109/icaect63952.2025.10958827.

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Mahalingam M, Sankara, N. Suresh Kumar, Amal Sivan, Shivam Kumar, Alok Kumar, and Anish Anand. "Next-Gen Home Security Framework with Facial Recognition and IoT Integration." In 2024 International Conference on Sustainable Communication Networks and Application (ICSCNA). IEEE, 2024. https://doi.org/10.1109/icscna63714.2024.10864217.

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S, Madura, Janani S, and V. R. Kanagavalli. "Smart Home Security System with Integrated Motion Detection and Facial Recognition." In 2024 International Conference on Smart Technologies for Sustainable Development Goals (ICSTSDG). IEEE, 2024. https://doi.org/10.1109/icstsdg61998.2024.11026660.

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Raporty organizacyjne na temat "Facial recognition security"

Eastman, Brittany. Legal Issues Facing Automated Vehicles, Facial Recognition, and Privacy Rights. SAE International, 2022. http://dx.doi.org/10.4271/epr2022016.

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Facial recognition software (FRS) is a form of biometric security that detects a face, analyzes it, converts it to data, and then matches it with images in a database. This technology is currently being used in vehicles for safety and convenience features, such as detecting driver fatigue, ensuring ride share drivers are wearing a face covering, or unlocking the vehicle. Public transportation hubs can also use FRS to identify missing persons, intercept domestic terrorism, deter theft, and achieve other security initiatives. However, biometric data is sensitive and there are numerous remaining

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