Relevant bibliographies by topics / Biometrics; Modalities; Face recognition

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Biometrics; Modalities; Face recognition'

Author: Grafiati
Published: 3 June 2025
Last updated: 31 July 2025

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Journal articles on the topic "Biometrics; Modalities; Face recognition"

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Rohini, B.R., and G. Dr.Thippeswamy. "BIOMETRICS-A PRELIMINARY APPROACH." International Journal of Research - Granthaalayah 5, no. 4 RACSIT (2017): 47–52. https://doi.org/10.5281/zenodo.572294.

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Authentication plays a vital role in Information security. The need for identification of legitimate user has increased in the waking concerns for global security. Biometric recognition Systems is a major tool for Authentication mechanism. Biometrics is the ability to identify and authenticate an individual using one or more of their behavioral or physical characteristics. The Study of Different Biometric Modalities gives a better understanding of Biometric Techniques. We focus our Study on Face Biometrics. This paper emphasizes on better understanding of introduction to Biometrics, Biometric
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B.R., Rohini, and Thippeswamy G. "BIOMETRICS-A PRELIMINARY APPROACH." International Journal of Research -GRANTHAALAYAH 5, no. 4RACSIT (2017): 47–52. http://dx.doi.org/10.29121/granthaalayah.v5.i4racsit.2017.3350.

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Authentication plays a vital role in Information security. The need for identification of legitimate user has increased in the waking concerns for global security. Biometric recognition Systems is a major tool for Authentication mechanism. Biometrics is the ability to identify and authenticate an individual using one or more of their behavioral or physical characteristics. The Study of Different Biometric Modalities gives a better understanding of Biometric Techniques. We focus our Study on Face Biometrics. This paper emphasizes on better understanding of introduction to Biometrics, Biometric
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D S, Dr Dinesh Kumar. "Human Authentication using Face, Voice and Fingerprint Biometrics." International Journal for Research in Applied Science and Engineering Technology 9, no. VII (2021): 853–62. http://dx.doi.org/10.22214/ijraset.2021.36381.

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Multimodal biometric approaches are growing in importance for personal verification and identification, since they provide better recognition results and hence improve security compared to biometrics based on a single modality. In this project, we present a multimodal biometric system that is based on the fusion of face, voice and fingerprint biometrics. For face recognition, we employ Haar Cascade Algorithm, while minutiae extraction is used for fingerprint recognition and we will be having a stored code word for the voice authentication, if any of these two authentication becomes true, the s
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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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Drosou, A., D. Ioannidis, K. Moustakas, and D. Tzovaras. "Unobtrusive Behavioral and Activity-Related Multimodal Biometrics: The ACTIBIO Authentication Concept." Scientific World JOURNAL 11 (2011): 503–19. http://dx.doi.org/10.1100/tsw.2011.51.

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Unobtrusive Authentication Using ACTIvity-Related and Soft BIOmetrics (ACTIBIO) is an EU Specific Targeted Research Project (STREP) where new types of biometrics are combined with state-of-the-art unobtrusive technologies in order to enhance security in a wide spectrum of applications. The project aims to develop a modular, robust, multimodal biometrics security authentication and monitoring system, which uses a biodynamic physiological profile, unique for each individual, and advancements of the state of the art in unobtrusive behavioral and other biometrics, such as face, gait recognition, a
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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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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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Singh, Law Kumar, Munish Khanna, and Hitendra Garg. "Multimodal Biometric Based on Fusion of Ridge Features with Minutiae Features and Face Features." International Journal of Information System Modeling and Design 11, no. 1 (2020): 37–57. http://dx.doi.org/10.4018/ijismd.2020010103.

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Multimodal biometrics refers to the exploiting combination of two or more biometric modalities in an identification of a system. Fingerprint, face, retina, iris, hand geometry, DNA, and palm print are physiological traits while voice, signature, keystrokes, gait are behavioural traits used for identification by a system. Single biometric features like faces, fingerprints, irises, retinas, etc., deteriorate or change with time, environment, user mode, physiological defects, and circumstance therefore integrating multi features of biometric traits increase robustness of the system. The proposed
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Ammour, Basma, Larbi Boubchir, Toufik Bouden, and Messaoud Ramdani. "Face–Iris Multimodal Biometric Identification System." Electronics 9, no. 1 (2020): 85. http://dx.doi.org/10.3390/electronics9010085.

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Multimodal biometrics technology has recently gained interest due to its capacity to overcome certain inherent limitations of the single biometric modalities and to improve the overall recognition rate. A common biometric recognition system consists of sensing, feature extraction, and matching modules. The robustness of the system depends much more on the reliability to extract relevant information from the single biometric traits. This paper proposes a new feature extraction technique for a multimodal biometric system using face–iris traits. The iris feature extraction is carried out using an
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Shetkar, Dr. Sharanbasappa, Baswaraj Gadgay, and D. C. Shubhangi. "Advancements in Face Recognition Using Deep Learning Techniques A Comprehensive Review." Journal of Harbin Engineering University 45, no. 3 (2024): 566–71. https://doi.org/10.5281/zenodo.10926464.

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This paper presents a comprehensive overview of recent developments in face recognition using&nbsp;deep learning approaches. We discuss the evolution of deep learning architectures for face recognition,&nbsp;including variations of CNNs such as Siamese networks, triplet loss networks, and attention mechanisms.&nbsp;Furthermore, we explore the challenges and strategies associated with training deep learning models for face&nbsp;recognition tasks, including data augmentation, transfer learning, and domain adaptation. Additionally, we&nbsp;highlight recent advancements in face recognition applica
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Dissertations / Theses on the topic "Biometrics; Modalities; Face recognition"

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Ding, Huaxiong. "Combining 2D facial texture and 3D face morphology for estimating people's soft biometrics and recognizing facial expressions." Thesis, Lyon, 2016. http://www.theses.fr/2016LYSEC061/document.

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Puisque les traits de biométrie douce peuvent fournir des preuves supplémentaires pour aider à déterminer précisément l’identité de l’homme, il y a eu une attention croissante sur la reconnaissance faciale basée sur les biométrie douce ces dernières années. Parmi tous les biométries douces, le sexe et l’ethnicité sont les deux caractéristiques démographiques importantes pour les êtres humains et ils jouent un rôle très fondamental dans l’analyse de visage automatique. En attendant, la reconnaissance des expressions faciales est un autre challenge dans le domaine de l’analyse de visage en raiso
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Cadavid, Steven. "Human Identification Based on Three-Dimensional Ear and Face Models." Scholarly Repository, 2011. http://scholarlyrepository.miami.edu/oa_dissertations/516.

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We propose three biometric systems for performing 1) Multi-modal Three-Dimensional (3D) ear + Two-Dimensional (2D) face recognition, 2) 3D face recognition, and 3) hybrid 3D ear recognition combining local and holistic features. For the 3D ear component of the multi-modal system, uncalibrated video sequences are utilized to recover the 3D ear structure of each subject within a database. For a given subject, a series of frames is extracted from a video sequence and the Region-of-Interest (ROI) in each frame is independently reconstructed in 3D using Shape from Shading (SFS). A fidelity measure i
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Jones, Creed Farris III. "Color Face Recognition using Quaternionic Gabor Filters." Diss., Virginia Tech, 2004. http://hdl.handle.net/10919/26591.

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This dissertation reports the development of a technique for automated face recognition, using color images. One of the more powerful techniques for recognition of faces in monochromatic images has been extended to color by the use of hypercomplex numbers called quaternions. Two software implementations have been written of the new method and the analogous method for use on monochromatic images. Test results show that the new method is superior in accuracy to the analogous monochrome method. Although color images are generally collected, the great majority of published research efforts and
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Goswami, D. "Cross-spectral face recognition between near-infrared and visible light modalities." Thesis, University of Surrey, 2012. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.580573.

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In this thesis, improvement of face recognition performance with the use of images from the visible (VIS) and near-infrared (NIR) spectrum is attempted. Face recog- nition systems can be adversely affected by scenarios which encounter a significant amount of illumination variation across images of the same subject. Cross-spectral face recognition systems using images collected across the VIS and NIR spectrum can counter the ill-effects of illumination variation by standardising both sets of images. A novel preprocessing technique is proposed, which attempts the transformation of faces across b
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Dabbah, Mohammad A. "Non-reversible mathematical transforms for secure biometric face recognition." Thesis, University of Newcastle upon Tyne, 2008. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.548002.

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As the demand for higher and more sophisticated security solutions has dramatically increased, a trustworthy and a more intelligent authentication technology has to takeover. That is biometric authentication. Although biometrics provides promising solutions, it is still a pattern recognition and artificial intelligence grand challenge. More importantly, biometric data in itself are vulnerable and requires comprehensive protection that ensures their security at every stage of the authentication procedure including the processing stage. Without this protection biometric authentication cannot rep
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Sanderson, Conrad, and conradsand@ieee org. "Automatic Person Verification Using Speech and Face Information." Griffith University. School of Microelectronic Engineering, 2003. http://www4.gu.edu.au:8080/adt-root/public/adt-QGU20030422.105519.

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Identity verification systems are an important part of our every day life. A typical example is the Automatic Teller Machine (ATM) which employs a simple identity verification scheme: the user is asked to enter their secret password after inserting their ATM card; if the password matches the one prescribed to the card, the user is allowed access to their bank account. This scheme suffers from a major drawback: only the validity of the combination of a certain possession (the ATM card) and certain knowledge (the password) is verified. The ATM card can be lost or stolen, and the password can be
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Ramos, Sanchez M. Ulises. "Aspects of facial biometrics for verification of personal identity." Thesis, University of Surrey, 2000. http://epubs.surrey.ac.uk/792194/.

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Tompkins, Richard Cortland. "Multimodal recognition using simultaneous images of iris and face with opportunistic feature selection." University of Dayton / OhioLINK, 2011. http://rave.ohiolink.edu/etdc/view?acc_num=dayton1312222279.

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Chaudhari, Soumee. "Modelling Distance Functions Induced by Face Recognition Algorithms." Scholar Commons, 2004. https://scholarcommons.usf.edu/etd/990.

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Face recognition algorithms has in the past few years become a very active area of research in the fields of computer vision, image processing, and cognitive psychology. This has spawned various algorithms of different complexities. The concept of principal component analysis(PCA) is a popular mode of face recognition algorithm and has often been used to benchmark other face recognition algorithms for identification and verification scenarios. However in this thesis, we try to analyze different face recognition algorithms at a deeper level. The objective is to model the distances output by any
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Alex, Ann Theja. "Local Alignment of Gradient Features for Face Photo and Face Sketch Recognition." University of Dayton / OhioLINK, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=dayton1353372694.

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Books on the topic "Biometrics; Modalities; Face recognition"

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D, Woodward John. Biometrics. McGraw-Hill/Osborne, 2003.

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Jr, Woodward John D., Virginia State Crime Commission, and Rand Corporation, eds. Biometrics: A look at facial recognition. RAND, 2003.

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D, Woodward John. Super Bowl surveillance: Facing up to biometrics. RAND, Arroyo Center, 2001.

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Hammoud, Riad I. Face biometrics for personal identification: Multi-sensory multi-modal systems. Springer, 2007.

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1959-, Pugliese Joseph, ed. Biometrics: Bodies, technologies, biopolitics. Routledge, 2010.

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D, Woodward John. Biometrics: Facing up to terrorism. RAND, Arroyo Center, 2001.

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D, Woodward John. Biometrics: Facing up to terrorism. RAND, 2001.

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Biometric, Consortium Conference (2006 Baltimore MD). 2006 Biometrics Symposium: Special Session on Research at the Biometric Consortium Conference. IEEE, 2006.

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Unconstrained Face Recognition (International Series on Biometrics). Springer, 2005.

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Chellappa, Rama, Shaohua Kevin Zhou, and Wenyi Zhao. Unconstrained Face Recognition (International Series on Biometrics Book 5). Springer, 2006.

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Book chapters on the topic "Biometrics; Modalities; Face recognition"

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Zhang, David D. "Face Recognition." In Automated Biometrics. Springer US, 2000. http://dx.doi.org/10.1007/978-1-4615-4519-4_7.

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Jain, Anil K., Arun A. Ross, and Karthik Nandakumar. "Face Recognition." In Introduction to Biometrics. Springer US, 2011. http://dx.doi.org/10.1007/978-0-387-77326-1_3.

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Grother, Patrick, Dmytro Shevtsov, Elham Tabassi, and Andreas Wolf. "Face Recognition Standards." In Encyclopedia of Biometrics. Springer Berlin Heidelberg, 2014. http://dx.doi.org/10.1007/978-3-642-27733-7_237-2.

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Patel, Vishal M., Jie Ni, and Rama Chellappa. "Remote Face Recognition." In Encyclopedia of Biometrics. Springer US, 2014. http://dx.doi.org/10.1007/978-3-642-27733-7_9109-2.

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Martinez, Aleix M. "Face Recognition, Overview." In Encyclopedia of Biometrics. Springer US, 2009. http://dx.doi.org/10.1007/978-0-387-73003-5_84.

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Bebis, George. "Face Recognition, Thermal." In Encyclopedia of Biometrics. Springer US, 2009. http://dx.doi.org/10.1007/978-0-387-73003-5_95.

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Grother, Patrick, Dmytro Shevtsov, Elham Tabassi, and Andreas Wolf. "Face Recognition Standards." In Encyclopedia of Biometrics. Springer US, 2015. http://dx.doi.org/10.1007/978-1-4899-7488-4_237.

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Martinez, Aleix M. "Face Recognition, Overview." In Encyclopedia of Biometrics. Springer US, 2015. http://dx.doi.org/10.1007/978-1-4899-7488-4_84.

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Patel, Vishal M., Jie Ni, and Rama Chellappa. "Remote Face Recognition." In Encyclopedia of Biometrics. Springer US, 2015. http://dx.doi.org/10.1007/978-1-4899-7488-4_9109.

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Bebis, George. "Face Recognition, Thermal." In Encyclopedia of Biometrics. Springer US, 2015. http://dx.doi.org/10.1007/978-1-4899-7488-4_95.

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Conference papers on the topic "Biometrics; Modalities; Face recognition"

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Wang, Rui, Chuanfu Shen, Manuel J. Marin-Jimenez, George Q. Huang, and Shiqi Yu. "Cross-Modality Gait Recognition: Bridging LiDAR and Camera Modalities for Human Identification." In 2024 IEEE International Joint Conference on Biometrics (IJCB). IEEE, 2024. http://dx.doi.org/10.1109/ijcb62174.2024.10744428.

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Nanduri, Anirudh, and Rama Chellappa. "Template-based Multi-Domain Face Recognition." In 2024 IEEE International Joint Conference on Biometrics (IJCB). IEEE, 2024. http://dx.doi.org/10.1109/ijcb62174.2024.10744520.

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Dosi, Muskan, Udaybhan Rathore, Chiranjeev Chiranjeev, Akshay Agarwal, Richa Singh, and Mayank Vatsa. "Is Face Super Resolution Truly Pushing the Boundaries of Face Recognition?" In 2024 IEEE International Joint Conference on Biometrics (IJCB). IEEE, 2024. http://dx.doi.org/10.1109/ijcb62174.2024.10744440.

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Medvedev, Iurii, and Nuno Gonçalves. "MorFacing: A Benchmark for Estimation Face Recognition Robustness to Face Morphing Attacks." In 2024 IEEE International Joint Conference on Biometrics (IJCB). IEEE, 2024. http://dx.doi.org/10.1109/ijcb62174.2024.10744449.

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Linghu, Yu, Tiago de Freitas Pereira, Christophe Ecabert, Sébastien Marcel, and Manuel Günther. "Score Normalization for Demographic Fairness in Face Recognition." In 2024 IEEE International Joint Conference on Biometrics (IJCB). IEEE, 2024. http://dx.doi.org/10.1109/ijcb62174.2024.10744514.

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Zhang, Xinyi, and Manuel Günther. "Quo Vadis RankList-based System in Face Recognition?" In 2024 IEEE International Joint Conference on Biometrics (IJCB). IEEE, 2024. http://dx.doi.org/10.1109/ijcb62174.2024.10744489.

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Saadabadi, Mohammad Saeed Ebrahimi, Sahar Rahimi Malakshan, Seyed Rasoul Hosseini, and Nasser M. Nasrabadi. "Boosting Unconstrained Face Recognition with Targeted Style Adversary." In 2024 IEEE International Joint Conference on Biometrics (IJCB). IEEE, 2024. http://dx.doi.org/10.1109/ijcb62174.2024.10744533.

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Buyssens, Pierre, and Marinette Revenu. "Fusion levels of visible and infrared modalities for face recognition." In 2010 IEEE Fourth International Conference On Biometrics: Theory, Applications And Systems (BTAS). IEEE, 2010. http://dx.doi.org/10.1109/btas.2010.5634542.

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Buyssens, Pierre, Marinette Revenu, and Olivier Lepetit. "Fusion of IR and visible light modalities for face recognition." In 2009 IEEE 3rd International Conference on Biometrics: Theory, Applications, and Systems (BTAS). IEEE, 2009. http://dx.doi.org/10.1109/btas.2009.5339031.

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Chowdhury, Anurag, Yousef Atoum, Luan Tran, Xiaoming Liu, and Arun Ross. "MSU-AVIS dataset: Fusing Face and Voice Modalities for Biometric Recognition in Indoor Surveillance Videos." In 2018 24th International Conference on Pattern Recognition (ICPR). IEEE, 2018. http://dx.doi.org/10.1109/icpr.2018.8545260.

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Reports on the topic "Biometrics; Modalities; Face recognition"

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Тарасова, Олена Юріївна, and Ірина Сергіївна Мінтій. Web application for facial wrinkle recognition. Кривий Ріг, КДПУ, 2022. http://dx.doi.org/10.31812/123456789/7012.

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Facial recognition technology is named one of the main trends of recent years. It’s wide range of applications, such as access control, biometrics, video surveillance and many other interactive humanmachine systems. Facial landmarks can be described as key characteristics of the human face. Commonly found landmarks are, for example, eyes, nose or mouth corners. Analyzing these key points is useful for a variety of computer vision use cases, including biometrics, face tracking, or emotion detection. Different methods produce different facial landmarks. Some methods use only basic facial landmar
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