Relevant bibliographies by topics / FACE RECOGNITION TECHNIQUES

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

Academic literature on the topic 'FACE RECOGNITION TECHNIQUES'

Author: Grafiati
Published: 11 September 2023
Last updated: 25 July 2025

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Journal articles on the topic "FACE RECOGNITION TECHNIQUES"

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Priya, B. Lakshmi, and Dr M. Pushpa Rani Rani. "Face Recognition System Techniques and Approaches." Indian Journal of Applied Research 4, no. 4 (2011): 109–13. http://dx.doi.org/10.15373/2249555x/apr2014/32.

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Romanyuk, Olexandr N., Sergey I. Vyatkin, Sergii V. Pavlov, Pavlo I. Mykhaylov, Roman Y. Chekhmestruk, and Ivan V. Perun. "FACE RECOGNITION TECHNIQUES." Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska 10, no. 1 (2020): 52–57. http://dx.doi.org/10.35784/iapgos.922.

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The problem of face recognition is discussed. The main methods of recognition are considered. The calibrated stereo pair for the face and calculating the depth map by the correlation algorithm are used. As a result, a 3D mask of the face is obtained. Using three anthropomorphic points, then constructed a coordinate system that ensures a possibility of superposition of the tested mask.
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Kushwah, Prashant. "FACE RECOGNITION WITH HYBRID TECHNIQUES." International Journal of Engineering Technologies and Management Research 5, no. 2 (2020): 178–87. http://dx.doi.org/10.29121/ijetmr.v5.i2.2018.642.

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Face recognition framework is still in test by numerous applications particularly in close perception and in security frameworks. Generally all utilizations of face recognition utilize enormous information sets, making challenges in present time preparing and effectiveness. This paper contains a structure to enhance face recognition framework which have a few phases. For good result in face recognition framework a few upgrades are critical at each stage. A novel plan is displayed in this paper which gives the better execution for face recognition framework. This plan incorporates expanding in
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Prashant, Kushwah. "FACE RECOGNITION WITH HYBRID TECHNIQUES." INTERNATIONAL JOURNAL OF ENGINEERING TECHNOLOGIES AND MANAGEMENT RESEARCH 5, no. 2 :SE (2018): 178–87. https://doi.org/10.5281/zenodo.1202126.

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Face recognition framework is still in test by numerous applications particularly in close perception and in security frameworks. Generally all utilizations of face recognition utilize enormous information sets, making challenges in present time preparing and effectiveness. This paper contains a structure to enhance face recognition framework which have a few phases. For good result in face recognition framework a few upgrades are critical at each stage. A novel plan is displayed in this paper which gives the better execution for face recognition framework. This plan incorporates expanding in
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jayakumari, V. Vi. "Face Recognition Techniques: A Survey." World Journal of Computer Application and Technology 1, no. 2 (2013): 41–50. http://dx.doi.org/10.13189/wjcat.2013.010204.

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Kaur, Mandeep, and Jasjit Kaur. "Review of Face Recognition Techniques." International Journal of Computer Applications 164, no. 6 (2017): 31–35. http://dx.doi.org/10.5120/ijca2017913731.

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Taqdir, Taqdir, and Dr Renu Dhir. "Face Recognition Techniques - A Review." IOSR Journal of Computer Engineering 16, no. 2 (2014): 23–27. http://dx.doi.org/10.9790/0661-162102327.

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Somani, Ms Jayashree S. "Face Recognition Techniques: A Survey." International Journal for Research in Applied Science and Engineering Technology 7, no. 6 (2019): 2498–502. http://dx.doi.org/10.22214/ijraset.2019.6420.

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Noori Hashim, Asaad, and Nedaa Kream Shalan. "Face Recognition using Hybrid Techniques." Journal of Engineering and Applied Sciences 14, no. 12 (2019): 4158–63. http://dx.doi.org/10.36478/jeasci.2019.4158.4163.

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Solanki, Kamini, and Prashant Pittalia. "Review of Face Recognition Techniques." International Journal of Computer Applications 133, no. 12 (2016): 20–24. http://dx.doi.org/10.5120/ijca2016907994.

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Dissertations / Theses on the topic "FACE RECOGNITION TECHNIQUES"

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Ebrahimpour-Komleh, Hossein. "Fractal techniques for face recognition." Thesis, Queensland University of Technology, 2006. https://eprints.qut.edu.au/16289/1/Hossein_Ebrahimpour-Komleh_Thesis.pdf.

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Fractals are popular because of their ability to create complex images using only several simple codes. This is possible by capturing image redundancy and presenting the image in compressed form using the self similarity feature. For many years fractals were used for image compression. In the last few years they have also been used for face recognition. In this research we present new fractal methods for recognition, especially human face recognition. This research introduces three new methods for using fractals for face recognition, the use of fractal codes directly as features, Fracta
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Ebrahimpour-Komleh, Hossein. "Fractal techniques for face recognition." Queensland University of Technology, 2006. http://eprints.qut.edu.au/16289/.

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Fractals are popular because of their ability to create complex images using only several simple codes. This is possible by capturing image redundancy and presenting the image in compressed form using the self similarity feature. For many years fractals were used for image compression. In the last few years they have also been used for face recognition. In this research we present new fractal methods for recognition, especially human face recognition. This research introduces three new methods for using fractals for face recognition, the use of fractal codes directly as features, Fracta
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Heseltine, Thomas David. "Face recognition : two-dimensional and three-dimensional techniques." Thesis, University of York, 2005. http://etheses.whiterose.ac.uk/9880/.

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Sun, Yunlian <1986&gt. "Advanced Techniques for Face Recognition under Challenging Environments." Doctoral thesis, Alma Mater Studiorum - Università di Bologna, 2014. http://amsdottorato.unibo.it/6355/1/sun_yunlian_tesi.pdf.

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Automatically recognizing faces captured under uncontrolled environments has always been a challenging topic in the past decades. In this work, we investigate cohort score normalization that has been widely used in biometric verification as means to improve the robustness of face recognition under challenging environments. In particular, we introduce cohort score normalization into undersampled face recognition problem. Further, we develop an effective cohort normalization method specifically for the unconstrained face pair matching problem. Extensive experiments conducted on several well know
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Sun, Yunlian <1986&gt. "Advanced Techniques for Face Recognition under Challenging Environments." Doctoral thesis, Alma Mater Studiorum - Università di Bologna, 2014. http://amsdottorato.unibo.it/6355/.

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Automatically recognizing faces captured under uncontrolled environments has always been a challenging topic in the past decades. In this work, we investigate cohort score normalization that has been widely used in biometric verification as means to improve the robustness of face recognition under challenging environments. In particular, we introduce cohort score normalization into undersampled face recognition problem. Further, we develop an effective cohort normalization method specifically for the unconstrained face pair matching problem. Extensive experiments conducted on several well know
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Gul, Ahmet Bahtiyar. "Holistic Face Recognition By Dimension Reduction." Master's thesis, METU, 2003. http://etd.lib.metu.edu.tr/upload/1056738/index.pdf.

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Face recognition is a popular research area where there are different approaches studied in the literature. In this thesis, a holistic Principal Component Analysis (PCA) based method, namely Eigenface method is studied in detail and three of the methods based on the Eigenface method are compared. These are the Bayesian PCA where Bayesian classifier is applied after dimension reduction with PCA, the Subspace Linear Discriminant Analysis (LDA) where LDA is applied after PCA and Eigenface where Nearest Mean Classifier applied after PCA. All the three methods are implemented on the Olivetti Resear
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Mian, Ajmal Saeed. "Representations and matching techniques for 3D free-form object and face recognition." University of Western Australia. School of Computer Science and Software Engineering, 2007. http://theses.library.uwa.edu.au/adt-WU2007.0046.

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[Truncated abstract] The aim of visual recognition is to identify objects in a scene and estimate their pose. Object recognition from 2D images is sensitive to illumination, pose, clutter and occlusions. Object recognition from range data on the other hand does not suffer from these limitations. An important paradigm of recognition is model-based whereby 3D models of objects are constructed offline and saved in a database, using a suitable representation. During online recognition, a similar representation of a scene is matched with the database for recognizing objects present in the scene . .
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Mian, Ajmal Saeed. "Representations and matching techniques for 3D free-form object and face recognition /." Connect to this title, 2006. http://theses.library.uwa.edu.au/adt-WU2007.0046.

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Al-Qatawneh, Sokyna M. S. "3D Facial Feature Extraction and Recognition. An investigation of 3D face recognition: correction and normalisation of the facial data, extraction of facial features and classification using machine learning techniques." Thesis, University of Bradford, 2010. http://hdl.handle.net/10454/4876.

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Face recognition research using automatic or semi-automatic techniques has emerged over the last two decades. One reason for growing interest in this topic is the wide range of possible applications for face recognition systems. Another reason is the emergence of affordable hardware, supporting digital photography and video, which have made the acquisition of high-quality and high resolution 2D images much more ubiquitous. However, 2D recognition systems are sensitive to subject pose and illumination variations and 3D face recognition which is not directly affected by such environmental change
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Han, Xia. "Towards the Development of an Efficient Integrated 3D Face Recognition System. Enhanced Face Recognition Based on Techniques Relating to Curvature Analysis, Gender Classification and Facial Expressions." Thesis, University of Bradford, 2011. http://hdl.handle.net/10454/5347.

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The purpose of this research was to enhance the methods towards the development of an efficient three dimensional face recognition system. More specifically, one of our aims was to investigate how the use of curvature of the diagonal profiles, extracted from 3D facial geometry models can help the neutral face recognition processes. Another aim was to use a gender classifier employed on 3D facial geometry in order to reduce the search space of the database on which facial recognition is performed. 3D facial geometry with facial expression possesses considerable challenges when it comes face rec
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Books on the topic "FACE RECOGNITION TECHNIQUES"

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1954-, Zhang Yu-Jin, ed. Advances in face image analysis: Techniques and technologies. Medical Information Science Reference, 2010.

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Jain, L. C., U. Halici, I. Hayashi, S. B. Lee, and S. Tsutsui. INTELLIGENT BIOMETRIC TECHNIQUES in FINGERPRINT and FACE RECOGNITION. Routledge, 2022. http://dx.doi.org/10.1201/9780203750520.

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M, Newton Elaine, and Information Technology Laboratory (National Institute of Standards and Technology). Mathematical and Computational Sciences Division, eds. Meta-analysis of face recognition algorithms. U.S. Dept. of Commerce, Technology Administration, Mathematics and Computational Sciences Division, National Institute of Standards and Technology, 2001.

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M, Newton Elaine, and Information Technology Laboratory (National Institute of Standards and Technology). Mathematical and Computational Sciences Division., eds. Meta-analysis of face recognition algorithms. U.S. Dept. of Commerce, Technology Administration, Mathematics and Computational Sciences Division, National Institute of Standards and Technology, 2001.

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M, Newton Elaine, and Information Technology Laboratory (National Institute of Standards and Technology). Mathematical and Computational Sciences Division., eds. Meta-analysis of face recognition algorithms. U.S. Dept. of Commerce, Technology Administration, Mathematics and Computational Sciences Division, National Institute of Standards and Technology, 2001.

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Elaine, Newton, and Information Technology Laboratory (National Institute of Standards and Technology). Mathematical and Computational Sciences Division, eds. Meta-analysis of face recognition algorithms. U.S. Dept. of Commerce, Technology Administration, Mathematics and Computational Sciences Division, National Institute of Standards and Technology, 2001.

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Yang, Ming-Hsuan. Face Detection and Gesture Recognition for Human-Computer Interaction. Springer US, 2001.

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1950-, Ahuja Narendra, ed. Face detection and gesture recognition for human-computer interaction. Kluwer Academic, 2001.

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Wiskott, Laurenz. Labeled graphs and dynamic link matching for face recognition and scene analysis. Deutsch, 1995.

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International Conference on Automatic Face and Gesture Recognition (5th 2002 Washington, D.C.). Fifth IEEE International Conference on Automatic Face and Gesture Recognition: Proceedings : 20-21 May, 2002, Washington, D.C. IEEE Computer Society, 2002.

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Book chapters on the topic "FACE RECOGNITION TECHNIQUES"

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Zhang, Yu-Jin. "Face Recognition." In A Selection of Image Analysis Techniques. CRC Press, 2022. http://dx.doi.org/10.1201/b23131-7.

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Tistarelli, Massimo, and Enrico Grosso. "Active Vision-based Face Recognition: Issues, Applications and Techniques." In Face Recognition. Springer Berlin Heidelberg, 1998. http://dx.doi.org/10.1007/978-3-642-72201-1_14.

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Bamba, Inshita, Yashika, Jahanvi Singh, and Pronika Chawla. "Face Recognition Techniques and Implementation." In Emerging Technologies in Data Mining and Information Security. Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-4052-1_35.

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Howell, A. Jonathan. "Introduction to Face Recognition." In INTELLIGENT BIOMETRIC TECHNIQUES in FINGERPRINT and FACE RECOGNITION. Routledge, 2022. http://dx.doi.org/10.1201/9780203750520-7.

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Azmeen, Juhika, and Dibya Jyoti Borah. "Face Recognition Techniques, Challenges: A Review." In Soft Computing for Intelligent Systems. Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-1048-6_27.

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Dharavath, K., F. A. Talukdar, R. H. Laskar, and N. Dey. "Face Recognition Under Dry and Wet Face Conditions." In Intelligent Techniques in Signal Processing for Multimedia Security. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-44790-2_12.

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Würtz, Rolf P. "Face Recognition from Correspondence Maps." In INTELLIGENT BIOMETRIC TECHNIQUES in FINGERPRINT and FACE RECOGNITION. Routledge, 2022. http://dx.doi.org/10.1201/9780203750520-10.

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Pandya, A. S., and R. R. Szabo. "Neural Networks for Face Recognition." In INTELLIGENT BIOMETRIC TECHNIQUES in FINGERPRINT and FACE RECOGNITION. Routledge, 2022. http://dx.doi.org/10.1201/9780203750520-8.

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Deriche, Mohamed, and Mohammed Aleemuddin. "Pose-Invariant Face Recognition Using Subspace Techniques." In Computer-Aided Intelligent Recognition Techniques and Applications. John Wiley & Sons, Ltd, 2005. http://dx.doi.org/10.1002/0470094168.ch11.

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Halici, U., L. C. Jain, and A. Erol. "Introduction to Fingerprint Recognition." In INTELLIGENT BIOMETRIC TECHNIQUES in FINGERPRINT and FACE RECOGNITION. Routledge, 2022. http://dx.doi.org/10.1201/9780203750520-1.

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Conference papers on the topic "FACE RECOGNITION TECHNIQUES"

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Al-Dilami, Redwan, Ammer T. Zahary, Abobakr Al-Sharafi, Osamah Al-Anashi, and Suliman Maresh. "Face Recognition Approach Using the Deep Learning Techniques." In 2024 1st International Conference on Emerging Technologies for Dependable Internet of Things (ICETI). IEEE, 2024. https://doi.org/10.1109/iceti63946.2024.10777116.

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Yang, Bingcan, and Xiai Chen. "Face Recognition Implementation Based on Image Processing Techniques." In 2024 2nd International Conference on Signal Processing and Intelligent Computing (SPIC). IEEE, 2024. http://dx.doi.org/10.1109/spic62469.2024.10691607.

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Aishwarya, M., and M. R. Pooja. "Advancements in Face Sketch Recognition: Techniques and Challenges." In 2024 IEEE Conference on Engineering Informatics (ICEI). IEEE, 2024. https://doi.org/10.1109/icei64305.2024.10912240.

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Kaur, Amarinder, Sudha Shanker Prasad, Rachit Garg, Sudhanshu Maurya, Ajay Kumar Yadav, and Deepak Suresh Asudani. "Face Recognition and Detection Using Machine Learning Techniques." In 2024 International Conference on Emerging Technologies and Innovation for Sustainability (EmergIN). IEEE, 2024. https://doi.org/10.1109/emergin63207.2024.10961240.

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Dai, Bo, Dengsheng Zhang, Hui Liu, Shixin Sun, and Ke Li. "Evaluation of face recognition techniques." In International Conference on Photonics and Image in Agriculture Engineering (PIAGENG 2009), edited by Honghua Tan and Qi Luo. SPIE, 2009. http://dx.doi.org/10.1117/12.836686.

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Sahu, Madhusmita, and Rasmita Dash. "Study on Face Recognition Techniques." In 2020 International Conference on Communication and Signal Processing (ICCSP). IEEE, 2020. http://dx.doi.org/10.1109/iccsp48568.2020.9182358.

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Prabhu Teja, G., and S. Ravi. "Face recognition using subspaces techniques." In 2012 International Conference on Recent Trends in Information Technology (ICRTIT). IEEE, 2012. http://dx.doi.org/10.1109/icrtit.2012.6206780.

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Giovani, Vanessa, Ivyna Johansen, Dea Asya Ashilla, and Novita Hanafiah. "Study on Face Recognition Techniques." In 2021 1st International Conference on Computer Science and Artificial Intelligence (ICCSAI). IEEE, 2021. http://dx.doi.org/10.1109/iccsai53272.2021.9609759.

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Hemathilaka, Susith, and Achala Aponso. "An Analysis of Face Recognition under Face Mask Occlusions." In 2nd International Conference on Machine Learning Techniques and Data Science (MLDS 2021). Academy and Industry Research Collaboration Center (AIRCC), 2021. http://dx.doi.org/10.5121/csit.2021.111804.

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The face mask is an essential sanitaryware in daily lives growing during the pandemic period and is a big threat to current face recognition systems. The masks destroy a lot of details in a large area of face and it makes it difficult to recognize them even for humans. The evaluation report shows the difficulty well when recognizing masked faces. Rapid development and breakthrough of deep learning in the recent past have witnessed most promising results from face recognition algorithms. But they fail to perform far from satisfactory levels in the unconstrained environment during the challenges
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Boubeguira, Zeyneb, and Salim Ghanemi. "GPU-based Face Recognition Acceleration Techniques." In the Fourth International Conference. ACM Press, 2018. http://dx.doi.org/10.1145/3234698.3234744.

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Reports on the topic "FACE RECOGNITION TECHNIQUES"

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Kroll, Joshua A. ACM TechBrief: Facial Recognition Technology. ACM, 2022. http://dx.doi.org/10.1145/3520137.

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Facial recognition is not a monolithic technology or a particular technique. Rather, facial recognition refers to any technology that automatically processes and purports to identify faces in images or videos. While humans interpret faces easily, computers must extract patterns from data or humans must code patterns into the system. Applying these patterns yields the facial descriptors (often referred to as faceprints) on which facial recognition systems rely to achieve their function.
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Scarrott, Rory, Cathal O'Mahony, Michael Sweeney, et al. KETmaritime: Setting course to energise maritime uptake of Key Enabling Technologies. University College Cork, 2020. http://dx.doi.org/10.33178/10468.10928.

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Key Enabled Technologies(KETs) have the potential to impact on many aspects of society, whilst transforming European industrial competitiveness at the local, national, and global scales. Studies funded by the European Commission have shown that European advances in six technology areas would not only enhance the leadership and competitiveness of European business, but also drive advances across Europe’s business sectors and society. Despite their applicability across sectors, KETs represent a change, and a new manner of moving forward. Business and society view change both positively, welcomin
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Meidan, Rina, and Robert Milvae. Regulation of Bovine Corpus Luteum Function. United States Department of Agriculture, 1995. http://dx.doi.org/10.32747/1995.7604935.bard.

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The main goal of this research plan was to elucidate regulatory mechanisms controlling the development, function of the bovine corpus luteum (CL). The CL contains two different sterodigenic cell types and therefore it was necessary to obtain pure cell population. A system was developed in which granulosa and theca interna cells, isolated from a preovulatory follicle, acquired characteristics typical of large (LL) and small (SL) luteal cells, respectively, as judged by several biochemical and morphological criteria. Experiments were conducted to determine the effects of granulosa cells removal
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Zeba, Mattia, Roberta Medda-Windischer, Andrea Carlà, and Alexandra Cosima Budabin. Civic Education as Preventive Measure and Inclusionary Practice. Glasgow Caledonian University, 2025. https://doi.org/10.59019/ddzh5n65.

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In the framework of the D.Rad project, WP10 – entitled Civic education as preventive measure and inclusionary practice – seeks to prevent youth radicalisation through civic education and to identify new pedagogical methods and interactive, participatory tools for building pro-social resilience to radical ideologies. We consider as ‘civic education programs’ all those initiatives of instruction that aim at affecting “people’s beliefs, commitments, capabilities, and actions as members or prospective members of communities”1, as well as foster critical thinking and promoting “civic engagement and
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