Gotowe bibliografie tematyczne / Biometric Fusion System

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  1. Artykuły w czasopismach
  2. Rozprawy doktorskie
  3. Części książek
  4. Streszczenia konferencji
  5. Raporty organizacyjne

Gotowa bibliografia na temat „Biometric Fusion System”

Autor: Grafiati
Data publikacji: 3 czerwca 2025
Data aktualizacji: 31 lipca 2025

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Artykuły w czasopismach na temat "Biometric Fusion System"

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Mrs., M. Tamil Selvi*1 &. Mrs. A. Sumathi 2. "FUSION TECHNIQUES FOR BIMODAL AND MULTIMODAL BIOMETRIC SYSTEM AUTHENTICATION." INTERNATIONAL JOURNAL OF ENGINEERING SCIENCES & RESEARCH TECHNOLOGY 6, no. 9 (2017): 40–45. https://doi.org/10.5281/zenodo.884845.

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Biometrics is the one of the security mechanism for computer network security. It is science and technology of measuring and analyzing biological data of human body, extracting details from the acquired data, and comparing the data to the stored in database. Existing system is unimodal biometric system. The proposed system is supported fusion techniques multimodal biometric system. However Multimodal biometrics requires storage of multiple biometric templates for each user, which results in increased risk to user privacy and system security. This paper will discuss the concept off biometrics,
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Mushtaque, Ahmed. "BIOMETRICS SYSTEM ACKNOWLEDGEMNT BASED ON DATA FUSION." International Journal of Research – Granthaalayah 4, no. 3 (2017): 85–91. https://doi.org/10.5281/zenodo.847003.

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In these days lot of systems have need an efficient and reliable biometrics recognition system. By considering the importance of biometric systems in global world, in this paper we are discussing the importance of a new era of verification. Applications of Biometric systems in accordance to Data fusion and what is the future of biometric systems.
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Abdoul, Kamal Assouma, Djara Tahirou, and Sobabe Abdou-Aziz. "Multi-Biometrics: Survey and Projection of a New Biometric System." International Journal of Engineering and Advanced Technology (IJEAT) 12, no. 3 (2023): 80–87. https://doi.org/10.35940/ijeat.C4008.0212323.

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<strong>Abstract: </strong>Multi-biometric systems using feature-level fusion allow more accuracy and reliability in recognition performance than uni-biometric systems. But in practice, this type of fusion is difficult to implement especially when we are facing heterogeneous biometric modalities or incompatible features. The major challenge of feature fusion is to produce a representation of each modality with an excellent level of discrimination. Beyond pure biometric modalities, the use of metadata has proven to improve the performance of biometric systems. In view of these findings, our wor
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Assouma, Abdoul Kamal, Tahirou Djara, and Abdou-Aziz Sobabe. "Multi-Biometrics: Survey and Projection of a New Biometric System." International Journal of Engineering and Advanced Technology 12, no. 3 (2023): 80–87. http://dx.doi.org/10.35940/ijeat.c4008.0212323.

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Multi-biometric systems using feature-level fusion allow more accuracy and reliability in recognition performance than uni-biometric systems. But in practice, this type of fusion is difficult to implement especially when we are facing heterogeneous biometric modalities or incompatible features. The major challenge of feature fusion is to produce a representation of each modality with an excellent level of discrimination. Beyond pure biometric modalities, the use of metadata has proven to improve the performance of biometric systems. In view of these findings, our work focuses on multi-origin b
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Medjahed, Chahreddine, Abdellatif Rahmoun, Christophe Charrier, and Freha Mezzoudj. "A deep learning-based multimodal biometric system using score fusion." IAES International Journal of Artificial Intelligence (IJ-AI) 11, no. 1 (2022): 65. http://dx.doi.org/10.11591/ijai.v11.i1.pp65-80.

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Recent trends in artificial intelligence tools-based biometrics have overwhelming attention to security matters. The hybrid approaches are motivated by the fact that they combine mutual strengths and they overcome their limitations. Such approaches are being applied to the fields of biomedical engineering. A biometric system uses behavioural or physiological characteristics to identify an individual. The fusion of two or more of these biometric unique characteristics contributes to improving the security and overcomes the drawbacks of unimodal biometric-based security systems. This work propos
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Chahreddine, Medjahed, Rahmoun Abdellatif, Charrier Christophe, and Mezzoudj Freha. "A deep learning-based multimodal biometric system using score fusion." International Journal of Artificial Intelligence (IJ-AI) 11, no. 1 (2022): 65–80. https://doi.org/10.11591/ijai.v11.i1.pp65-80.

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Recent trends in artificial intelligence tools-based biometrics have overwhelming attention to security matters. The hybrid approaches are motivated by the fact that they combine mutual strengths and they overcome their limitations. Such approaches are being applied to the fields of biomedical engineering. A biometric system uses behavioural or physiological characteristics to identify an individual. The fusion of two or more of these biometric unique characteristics contributes to improving the security and overcomes the drawbacks of unimodal biometric-based security systems. This work propos
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Omar, Bayan, Hamsa D. Majeed, Siti Zaiton Mohd Hashim, and Muzhir Al-Ani. "New Feature-level Algorithm for a Face-fingerprint Integral Multi-biometrics Identification System." UHD Journal of Science and Technology 6, no. 1 (2022): 12–20. http://dx.doi.org/10.21928/uhdjst.v6n1y2022.pp12-20.

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This article delves into the power of multi-biometric fusion for individual identification. a new feature-level algorithm is proposed that is the Dis-Eigen algorithm. Here, a feature-fusion framework is proposed for attaining better accuracy when identifying individuals for multiple biometrics. The framework, therefore, underpins the new multi-biometric system as it guides multi-biometric fusion applications at the feature phase for identifying individuals. In this regard, the Face-fingerprints of 20 individuals represented by 160 images were used in this framework . Experimental resultants of
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Snehlata, Barde. "Multimodal biometrics system with face, ear, and foot fusion techniques." i-manager’s Journal on Pattern Recognition 10, no. 2 (2023): 27. http://dx.doi.org/10.26634/jpr.10.2.20352.

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Biometrics, as an identification method, is used for various applications, particularly in security technologies. The integration of multiple biometric sources aims to overcome limitations observed in unimodal systems, enhancing recognition accuracy. Fusion techniques, categorized into sensor level, feature level, matching score level, decision level, and rank level, are explored to optimize the combination of information from different modalities. Various fusion schemes, such as feature-level fusion, decision-level fusion, and hybrid systems, are investigated for their effectiveness in integr
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Ghadeer, Ibrahim Maki, and Basim Abed Sarah. "Multimodal Biometric System Fusion Using Fingerprint and Iris with Convolutional Neural Network." Engineering and Technology Journal 9, no. 09 (2024): 5140–47. https://doi.org/10.5281/zenodo.13768197.

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Biometric sensing technology became everyday life frequent component as a result of world requirement for info security and safety legislation. A strong and efficient individual authentication has appeared because of new developments in multimodal biometrics. Multimodal biometrics integrates different biological traits in trying for creating considerable effect on identification performance. Latent fingerprint biometrics refer to effective human identification system for criminals given the accessible crime evidence shreds. Although, biometric trait restrictions like intra-class variation, sen
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Sujana, S., and V. S. K. Reddy. "Comparison of levels and fusion approaches for multimodal biometrics." Indonesian Journal of Electrical Engineering and Computer Science 23, no. 2 (2021): 791. http://dx.doi.org/10.11591/ijeecs.v23.i2.pp791-801.

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The biometric-based authentication system occupies maximal space in the field of security administration. Biometric applications are swiftly accelerating in day-to-day life such as computer login, smart homes, online banking, hospitals, border areas, industries, forensics, e-voting attendance system and investigation of crime. A reliable and accurate recognition body can be achieved with multimodal biometric methodologies. In this paper, we discuss starting with an introduction to biometric systems followed by their classification, and advantages as well as disadvantages. In today’s world, mos
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Rozprawy doktorskie na temat "Biometric Fusion System"

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Janečka, Petr. "Multimodální biometrický systém kombinující duhovku a sítnici." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2015. http://www.nusl.cz/ntk/nusl-234910.

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This diploma thesis focuses on multibiometric systems, specifically on biometric fusion. The thesis describes eye biometrics, i.e. recognition based on retina and iris. The key part consists of design and implementation specification of a biometric system based on retina and iris recognition.
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Mohamed, Abdul Cader Akmal Jahan. "Finger biometric system using bispectral invariants and information fusion techniques." Thesis, Queensland University of Technology, 2019. https://eprints.qut.edu.au/134464/1/Akmal%20Jahan_Mohamed%20Abdul%20Cader_Thesis.pdf.

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Contactless hand biometric systems are better accepted than contact prints as they are hygienic and accelerate data acquisition. This research is one of the few investigating contactless biometrics of the full hand by proposing a novel algorithm based on ridge orientation information along lines connecting key points, higher order spectral features, and fusion. It was investigated with contactless finger images acquired from 81 users, and found to be robust to hand orientation and image size, and provide acceptable performance using two fingers with fusion. The algorithm has potential to use i
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Assaad, Firas Souhail. "Biometric Multi-modal User Authentication System based on Ensemble Classifier." University of Toledo / OhioLINK, 2014. http://rave.ohiolink.edu/etdc/view?acc_num=toledo1418074931.

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Nandakumar, Karthik. "Multibiometric systems fusion strategies and template security /." Diss., Connect to online resource - MSU authorized users, 2008.

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Thesis (Ph. D.)--Michigan State University. Dept. of Computer Science and Engineering, 2008.<br>Title from PDF t.p. (viewed on Mar. 30, 2009) Includes bibliographical references (p. 210-228). Also issued in print.
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John, George Jacqueline. "Optimising multimodal fusion for biometric identification systems." Thesis, University of Kent, 2004. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.418551.

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Hájek, Josef. "Biometrický systém pro rozpoznávání podle sítnice a duhovky oka." Doctoral thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2017. http://www.nusl.cz/ntk/nusl-412584.

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Tato disertační práce se zabývá biometrickým a medicínským zařízením pro simultánní snímání duhovky a sítnice oka v jednom kroku. V případě biometrického zaměření je práce rozšířena o vzájemnou fúzi těchto dvou biometrik do jedné šablony, kdy multimodální systém vykazuje mnohem lepší parametry než systém unimodální, a to především ve větší unikátnosti, univerzálnosti a velmi obtížně proveditelnému útoku (až téměř nemožnému) na senzor. V případě medicínského využití práce dále rozvíjí detekci a klasifikaci nemocí pro základ expertního systému pro oftalmologické účely, který bude umožňovat pomoc
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Rodrigues, Ricardo Nagel. "Fusão biométrica com lógica nebulosa." [s.n.], 2006. http://repositorio.unicamp.br/jspui/handle/REPOSIP/259414.

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Orientador: Lee Luan Ling<br>Dissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Elétrica e de Computação<br>Made available in DSpace on 2018-08-17T04:05:46Z (GMT). No. of bitstreams: 1 Rodrigues_RicardoNagel_M.pdf: 1212348 bytes, checksum: c1f563f073688d610f7a7013a642214c (MD5) Previous issue date: 2006<br>Resumo: Neste trabalho, apresentamos um novo método para fazer a fusão de dois sistemas biométricos unimodais. O objetivo é gerar um sistema biométrico multimodal que apresente menores taxas de erro, maior robustez e maior segurança. O método proposto pode
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Phiri, Jackson. "A digital identity management system." Thesis, UWC, 2007. http://hdl.handle.net/11394/2871.

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>Magister Scientiae - MSc<br>The recent years have seen an increase in the number of users accessing online services using communication devices such as computers, mobile phones and cards based credentials such as credit cards. This has prompted most governments and business organizations to change the way they do business and manage their identity information. The coming of the online services has however made most Internet users vulnerable to identity fraud and theft. This has resulted in a subsequent increase in the number of reported cases of identity theft and fraud, which is on the incr
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"Decision fusion in a multimodal biometric system." 2004. http://library.cuhk.edu.hk/record=b5891972.

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Lau, Chun Wai.<br>Thesis (M.Phil.)--Chinese University of Hong Kong, 2004.<br>Includes bibliographical references (leaves 119-123).<br>Abstracts in English and Chinese.<br>Chapter 1 --- Introduction --- p.1<br>Chapter 1.1 --- Overview --- p.1<br>Chapter 1.2 --- Multimodal Biometric Systems --- p.3<br>Chapter 1.3 --- Objectives --- p.7<br>Chapter 1.4 --- Thesis Outline --- p.7<br>Chapter 2 --- Background --- p.9<br>Chapter 2.1 --- Decision Fusions in Multimodal Biometric Systems --- p.10<br>Chapter 2.2 --- Fuzzy Logic --- p.15<br>Chapter 2.2.1 --- Fuzzy Sets and Their Operations --- p.
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Chen, Yan-Ying, and 陳殷盈. "Audio-Visual Information Fusion for Biometric Verification System." Thesis, 2004. http://ndltd.ncl.edu.tw/handle/96602947378036041696.

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碩士<br>國立清華大學<br>資訊工程學系<br>92<br>Personal verification system has already been used in real-life at present. It becomes increasingly important recently and has been employed in many practical applications, including automatic teller machines, access control system and so on. Biometrics is unique and can be classified between different claims. Hence, Biometrics can replace password or ID card to build a verification system. The multi-modal biometric verification system comprised of multiple experts would be more robust and more accurate than a single-modal biometrics verification system. The p
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Części książek na temat "Biometric Fusion System"

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Dhole, Sampada, and Vinayak Bairagi. "Multimodal Biometric Identification Systems Using Sensor-Level Fusion." In Multimodal Biometric Identification System. Chapman and Hall/CRC, 2024. http://dx.doi.org/10.1201/9781032665993-6.

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Dhole, Sampada, and Vinayak Bairagi. "Multimodal Biometric Identification Systems Using Feature-Level Fusion." In Multimodal Biometric Identification System. Chapman and Hall/CRC, 2024. http://dx.doi.org/10.1201/9781032665993-7.

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Yang, Linlin, Dandan Du, Baochang Zhang, and Wankou Yang. "A Panoramic Video System Based on Exposure Adjustment and Non-linear Fusion." In Biometric Recognition. Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-25417-3_59.

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Viswanathan, P., P. Venkata Krishna, and S. Hariharan. "Multimodal Biometric Invariant Moment Fusion Authentication System." In Communications in Computer and Information Science. Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-12214-9_24.

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Modarresi, Morteza, and Iman Sheikh Oveisi. "A Contourlet Transform Based for Features Fusion in Retina and Iris Multimodal Biometric System." In Biometric Authentication. Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-13386-7_7.

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Fierrez-Aguilar, J., N. Alonso-Hermira, G. Moreno-Marquez, and J. Ortega-Garcia. "An Off-line Signature Verification System Based on Fusion of Local and Global Information." In Biometric Authentication. Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-25976-3_27.

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Kuśmierczyk, Aleksander, Martyna Sławińska, Kornel Żaba, and Khalid Saeed. "Biometric Fusion System Using Face and Voice Recognition." In Advances in Intelligent Systems and Computing. Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-8969-6_5.

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Chia, Chaw, Nasser Sherkat, and Lars Nolle. "Confidence Partition and Hybrid Fusion in Multimodal Biometric Verification System." In Biometric ID Management and Multimodal Communication. Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-04391-8_28.

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Dieckmann, U., P. Plankensteiner, R. Schamburger, B. Fröba, and S. Meller. "SESAM: A biometric person identification system using sensor fusion." In Audio- and Video-based Biometric Person Authentication. Springer Berlin Heidelberg, 1997. http://dx.doi.org/10.1007/bfb0016009.

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Gavrilova, Marina L., and Md Maruf Monwar. "Current Trends in Multimodal Biometric System—Rank Level Fusion." In Pattern Recognition, Machine Intelligence and Biometrics. Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-22407-2_25.

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Streszczenia konferencji na temat "Biometric Fusion System"

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P, Poovizhi, Pavithra D, Vijaya Kumar T, Nandhakumar M, Suryadharshini G, and Sheljin S G. "Multimodal Biometric Fusion System." In 2024 International Conference on Emerging Research in Computational Science (ICERCS). IEEE, 2024. https://doi.org/10.1109/icercs63125.2024.10895379.

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Rajalakshmi, M., Labeeb Khan, Abhijit R. Nair, and Rishita Seetha. "Enhanced Biometric Authentication System using Deep Learning-based Multimodal Fusion." In 2025 3rd International Conference on Self Sustainable Artificial Intelligence Systems (ICSSAS). IEEE, 2025. https://doi.org/10.1109/icssas66150.2025.11081036.

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Babu, Vunnava Dinesh, Raghunadha Reddi Dornala, Chamarty Anusha, Popuri Ramesh Babu, Kaja Krishna Mohan, and Kari Venkata Sumanth. "A Hybrid Multimodal Biometric Recognition System (HMBRS) based on Fusion of Iris, Face, and Finger Vein Traits." In 2024 5th International Conference on Smart Electronics and Communication (ICOSEC). IEEE, 2024. http://dx.doi.org/10.1109/icosec61587.2024.10722340.

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I, Yuvasri, Soundarya Devi K, Alwin Infant P, and Jainish G. R. "Multi-Modal Biometric Authentication System Using Hybrid Convolutional Neural Networks (HCNN) Based on Face, Finger Vein and Iris Fusion." In 2025 6th International Conference on Mobile Computing and Sustainable Informatics (ICMCSI). IEEE, 2025. https://doi.org/10.1109/icmcsi64620.2025.10883590.

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Hendrawan, Muhammad Afif, Noprianto, Maskur, and Sofyan Noor Arief. "Enhancing Biometric Identification Through EEG and ECG Fusion." In 2024 7th International Seminar on Research of Information Technology and Intelligent Systems (ISRITI). IEEE, 2024. https://doi.org/10.1109/isriti64779.2024.10963629.

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Gowravaram, Rashmi. "Analysis on Multimodal Biometric Classification based on Feature Level Fusion and Score Level Fusion Methods." In 2024 International Conference on Distributed Systems, Computer Networks and Cybersecurity (ICDSCNC). IEEE, 2024. https://doi.org/10.1109/icdscnc62492.2024.10939900.

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Kumar, Yogesh, Aditya Nigam, Kamlesh Tiwari, and Phalguni Gupta. "An automated multimodal biometric system and fusion." In 2014 IEEE Symposium on Computational Intelligence in Biometrics and Identity Management (CIBIM). IEEE, 2014. http://dx.doi.org/10.1109/cibim.2014.7015438.

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Garg, Suneet Narula, Renu Vig, and Savita Gupta. "Multimodal biometric system based on decision level fusion." In 2016 International conference on Signal Processing, Communication, Power and Embedded System (SCOPES). IEEE, 2016. http://dx.doi.org/10.1109/scopes.2016.7955540.

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Rane, Milind E., and Prameya P. Deshpande. "Multimodal Biometric Recognition System Using Feature Level Fusion." In 2018 Fourth International Conference on Computing Communication Control and Automation (ICCUBEA). IEEE, 2018. http://dx.doi.org/10.1109/iccubea.2018.8697821.

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Hwang, Dae Yon, Bilal Taha, and Dimitrios Hatzinakos. "Variation-Stable Fusion for PPG-Based Biometric System." In ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2021. http://dx.doi.org/10.1109/icassp39728.2021.9413906.

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Raporty organizacyjne na temat "Biometric Fusion System"

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Kulhandjian, Hovannes. Detecting Driver Drowsiness with Multi-Sensor Data Fusion Combined with Machine Learning. Mineta Transportation Institute, 2021. http://dx.doi.org/10.31979/mti.2021.2015.

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In this research work, we develop a drowsy driver detection system through the application of visual and radar sensors combined with machine learning. The system concept was derived from the desire to achieve a high level of driver safety through the prevention of potentially fatal accidents involving drowsy drivers. According to the National Highway Traffic Safety Administration, drowsy driving resulted in 50,000 injuries across 91,000 police-reported accidents, and a death toll of nearly 800 in 2017. The objective of this research work is to provide a working prototype of Advanced Driver Ass
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