Literatura académica sobre el tema "Pattern recognition applications"
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Artículos de revistas sobre el tema "Pattern recognition applications"
Mikhailov, Alexei. "Indexing-Based Pattern Recognition". Advanced Materials Research 403-408 (noviembre de 2011): 5254–59. http://dx.doi.org/10.4028/www.scientific.net/amr.403-408.5254.
Texto completoGrabusts, Peter. "POTENTIAL FUNCTION METHOD APPROACH TO PATTERN RECOGNITION APPLICATIONS". Environment. Technology. Resources. Proceedings of the International Scientific and Practical Conference 2 (15 de junio de 2017): 30. http://dx.doi.org/10.17770/etr2017vol2.2512.
Texto completoNezhad, Mohammad Saber Fallah. "Applications of Pattern Recognition Techniques in Social Science". Studies in Social Science & Humanities 2, n.º 1 (enero de 2023): 31–35. http://dx.doi.org/10.56397/sssh.2023.01.06.
Texto completoPAPAKOSTAS, G. A., Y. S. BOUTALIS, D. E. KOULOURIOTIS y B. G. MERTZIOS. "FUZZY COGNITIVE MAPS FOR PATTERN RECOGNITION APPLICATIONS". International Journal of Pattern Recognition and Artificial Intelligence 22, n.º 08 (diciembre de 2008): 1461–86. http://dx.doi.org/10.1142/s0218001408006910.
Texto completoKober, Vitaly, Tae Choi, Victor Diaz-Ramírez y Pablo Aguilar-González. "Pattern Recognition: Recent Advances and Applications". Mathematical Problems in Engineering 2018 (15 de noviembre de 2018): 1–2. http://dx.doi.org/10.1155/2018/8510319.
Texto completoRen, Dong y Simon X. Yang. "Intelligent Pattern Recognition Technology and Applications". Intelligent Automation & Soft Computing 19, n.º 4 (diciembre de 2013): 497–99. http://dx.doi.org/10.1080/10798587.2013.869107.
Texto completoPaolanti, Marina y Emanuele Frontoni. "Multidisciplinary Pattern Recognition applications: A review". Computer Science Review 37 (agosto de 2020): 100276. http://dx.doi.org/10.1016/j.cosrev.2020.100276.
Texto completoLavine, Barry K. "Environmental applications of pattern recognition techniques". Chemometrics and Intelligent Laboratory Systems 15, n.º 2-3 (agosto de 1992): 219–30. http://dx.doi.org/10.1016/0169-7439(92)85011-q.
Texto completoKrasnoproshin, V. V. y V. A. Obraztsov. "Pattern Recognition: Theoretical Research Experience and Applications". Pattern Recognition and Image Analysis 31, n.º 1 (enero de 2021): 163–71. http://dx.doi.org/10.1134/s1054661821010132.
Texto completoSilva, Francisco de Assis Tavares Ferreira da, Magno Prudêncio de Almeida Filho, Antonio Macilio Pereira de Lucena y Alexandre Guirland Nowosad. "Pattern recognition on FPGA for aerospace applications". Research, Society and Development 10, n.º 12 (14 de septiembre de 2021): e83101219181. http://dx.doi.org/10.33448/rsd-v10i12.19181.
Texto completoTesis sobre el tema "Pattern recognition applications"
Thompson, J. R. "Applications of pattern recognition in medicine". Thesis, Open University, 1985. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.377939.
Texto completoRobinson, Daniel D. "Applications of pattern recognition and pattern analysis to molecule design". Thesis, University of Oxford, 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.343465.
Texto completoPAOLANTI, MARINA. "Pattern Recognition for challenging Computer Vision Applications". Doctoral thesis, Università Politecnica delle Marche, 2018. http://hdl.handle.net/11566/252904.
Texto completoPattern Recognition is the study of how machines can observe the environment, learn to distinguish patterns of interest from their background, and make sound and reasonable decisions about the patterns categories. Nowadays, the application of Pattern Recognition algorithms and techniques is ubiquitous and transversal. With the recent advances in computer vision, we now have the ability to mine such massive visual data to obtain valuable insight about what is happening in the world. The availability of affordable and high resolution sensors (e.g., RGB-D cameras, microphones and scanners) and data sharing have resulted in huge repositories of digitized documents (text, speech, image and video). Starting from such a premise, this thesis addresses the topic of developing next generation Pattern Recognition systems for real applications such as Biology, Retail, Surveillance, Social Media Intelligence and Digital Cultural Heritage. The main goal is to develop computer vision applications in which Pattern Recognition is the key core in their design, starting from general methods, that can be exploited in more fields, and then passing to methods and techniques addressing specific problems. The privileged focus is on up-to-date applications of Pattern Recognition techniques to real-world problems, and on interdisciplinary research, experimental and/or theoretical studies yielding new insights that advance Pattern Recognition methods. The final ambition is to spur new research lines, especially within interdisciplinary research scenarios. Faced with many types of data, such as images, biological data and trajectories, a key difficulty was to nd relevant vectorial representations. While this problem had been often handled in an ad-hoc way by domain experts, it has proved useful to learn these representations directly from data, and Machine Learning algorithms, statistical methods and Deep Learning techniques have been particularly successful. The representations are then based on compositions of simple parameterized processing units, the depth coming from the large number of such compositions. It was desirable to develop new, efficient data representation or feature learning/indexing techniques, which can achieve promising performance in the related tasks. The overarching goal of this work consists of presenting a pipeline to select the model that best explains the given observations; nevertheless, it does not prioritize in memory and time complexity when matching models to observations. For the Pattern Recognition system design, the following steps are performed: data collection, features extraction, tailored learning approach and comparative analysis and assessment. The proposed applications open up a wealth of novel and important opportunities for the machine vision community. The newly dataset collected as well as the complex areas taken into exam, make the research challenging. In fact, it is crucial to evaluate the performance of state of the art methods to demonstrate their strength and weakness and help identify future research for designing more robust algorithms. For comprehensive performance evaluation, it is of great importance developing a library and benchmark to gauge the state of the art because the methods design that are tuned to a specic problem do not work properly on other problems. Furthermore, the dataset selection is needed from different application domains in order to offer the user the opportunity to prove the broad validity of methods. Intensive attention has been drawn to the exploration of tailored learning models and algorithms, and their extension to more application areas. The tailored methods, adopted for the development of the proposed applications, have shown to be capable of extracting complex statistical features and efficiently learning their representations, allowing it to generalize well across a wide variety of computer vision tasks, including image classication, text recognition and so on.
Hayes, William S. "Pattern recognition and signal detection in gene finding". Diss., Georgia Institute of Technology, 1998. http://hdl.handle.net/1853/25420.
Texto completoPrendergast, David Jeremy. "Applications of statistical pattern recognition in medical imaging". Thesis, University of Manchester, 1993. https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.629772.
Texto completoEvans, Fiona H. "Syntactic models with applications in image analysis /". [Perth, W.A.] : [University of W.A.], 2006. http://theses.library.uwa.edu.au/adt-WU2007.0001.
Texto completoYan, Wing-fai. "Eye movement measurement for clinical applications using pattern recognition /". [Hong Kong : University of Hong Kong], 1988. http://sunzi.lib.hku.hk/hkuto/record.jsp?B12434024.
Texto completoMa, Chengyuan. "A detection-based pattern recognition framework and its applications". Diss., Georgia Institute of Technology, 2010. http://hdl.handle.net/1853/33889.
Texto completo甄榮輝 y Wing-fai Yan. "Eye movement measurement for clinical applications using pattern recognition". Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 1988. http://hub.hku.hk/bib/B31209026.
Texto completoLopez-Bonilla, Roman Ernesto. "Object recognition in three-dimensions for robotic applications". Thesis, University of Bradford, 1990. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.305752.
Texto completoLibros sobre el tema "Pattern recognition applications"
Devijver, Pierre A. Pattern Recognition Theory and Applications. Berlin, Heidelberg: Springer Berlin Heidelberg, 1987.
Buscar texto completoFred, Ana, Maria De Marsico y Mário Figueiredo, eds. Pattern Recognition: Applications and Methods. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-27677-9.
Texto completoFred, Ana, Maria De Marsico y Gabriella Sanniti di Baja, eds. Pattern Recognition Applications and Methods. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-53375-9.
Texto completoDe Marsico, Maria, Gabriella Sanniti di Baja y Ana Fred, eds. Pattern Recognition Applications and Methods. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-05499-1.
Texto completoDe Marsico, Maria, Gabriella Sanniti di Baja y Ana Fred, eds. Pattern Recognition Applications and Methods. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-66125-0.
Texto completoFred, Ana y Maria De Marsico, eds. Pattern Recognition Applications and Methods. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-12610-4.
Texto completoDe Marsico, Maria, Gabriella Sanniti di Baja y Ana Fred, eds. Pattern Recognition Applications and Methods. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-93647-5.
Texto completoDevijver, Pierre A. y Josef Kittler, eds. Pattern Recognition Theory and Applications. Berlin, Heidelberg: Springer Berlin Heidelberg, 1987. http://dx.doi.org/10.1007/978-3-642-83069-3.
Texto completoLatorre Carmona, Pedro, J. Salvador Sánchez y Ana L. N. Fred, eds. Pattern Recognition - Applications and Methods. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-36530-0.
Texto completoDe Marsico, Maria, Gabriella Sanniti di Baja y Ana Fred, eds. Pattern Recognition Applications and Methods. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-40014-9.
Texto completoCapítulos de libros sobre el tema "Pattern recognition applications"
Croall, Ian F. y John P. Mason. "Pattern Recognition". En Industrial Applications of Neural Networks, 55–117. Berlin, Heidelberg: Springer Berlin Heidelberg, 1992. http://dx.doi.org/10.1007/978-3-642-84837-7_4.
Texto completoZimmermann, H. J. "Pattern Recognition". En Fuzzy Set Theory — and Its Applications, 217–40. Dordrecht: Springer Netherlands, 1991. http://dx.doi.org/10.1007/978-94-015-7949-0_11.
Texto completoZimmermann, H. J. "Pattern Recognition". En Fuzzy Set Theory — and Its Applications, 187–212. Dordrecht: Springer Netherlands, 1985. http://dx.doi.org/10.1007/978-94-015-7153-1_11.
Texto completoBunke, Horst, Peter Dickinson, Miro Kraetzl, Michel Neuhaus y Marc Stettler. "Matching of Hypergraphs — Algorithms, Applications, and Experiments". En Applied Pattern Recognition, 131–54. Berlin, Heidelberg: Springer Berlin Heidelberg, 2008. http://dx.doi.org/10.1007/978-3-540-76831-9_6.
Texto completoCristescu, Gabriela y Liana Lupşa. "Applications in pattern recognition". En Non-Connected Convexities and Applications, 227–46. Boston, MA: Springer US, 2002. http://dx.doi.org/10.1007/978-1-4615-0003-2_9.
Texto completoGökberk, Berk, Albert Ali Salah, Neşe Alyüz y Lale Akarun. "3D Face Recognition: Technology and Applications". En Advances in Pattern Recognition, 217–46. London: Springer London, 2009. http://dx.doi.org/10.1007/978-1-84882-385-3_9.
Texto completoYin, Xiaoxia, Brian W. H. Ng y Derek Abbott. "THz Pattern Recognition Experiments". En Terahertz Imaging for Biomedical Applications, 133–77. New York, NY: Springer New York, 2012. http://dx.doi.org/10.1007/978-1-4614-1821-4_9.
Texto completoFerrans, James C. y Jonathan Engelsma. "Software Architectures for Networked Mobile Speech Applications". En Advances in Pattern Recognition, 279–99. London: Springer London, 2008. http://dx.doi.org/10.1007/978-1-84800-143-5_13.
Texto completoWang, P. S. P. "Intelligent pattern recognition and applications". En Lecture Notes in Computer Science, 34–36. Berlin, Heidelberg: Springer Berlin Heidelberg, 1992. http://dx.doi.org/10.1007/3-540-56346-6_28.
Texto completoEvans, Brian J. "Pattern Recognition and Its Applications". En A Simple Guide to Technology and Analytics, 49–72. Boca Raton: Chapman and Hall/CRC, 2021. http://dx.doi.org/10.1201/9781003108443-3.
Texto completoActas de conferencias sobre el tema "Pattern recognition applications"
Wang, Patrick. "Intelligent pattern recognition and applications". En the First ACM International Conference. New York, New York, USA: ACM Press, 2010. http://dx.doi.org/10.1145/1854776.1854782.
Texto completoMartínez-Díaz, Saúl y Vitaly Kober. "Pattern recognition with adaptive nonlinear filters". En Optical Engineering + Applications, editado por Andrew G. Tescher. SPIE, 2007. http://dx.doi.org/10.1117/12.734240.
Texto completoKovács, Levente y Tamás Szirányi. "Recognition of hidden pattern with background". En Optical Engineering + Applications, editado por Oliver E. Drummond y Richard D. Teichgraeber. SPIE, 2007. http://dx.doi.org/10.1117/12.738512.
Texto completoCasacuberta, F. y A. Sanfeliu. "Advances in Pattern Recognition and Applications". En Vth Spanish Symposium on Pattern Recognition and Image Analysis. WORLD SCIENTIFIC, 1994. http://dx.doi.org/10.1142/9789814533928.
Texto completoKabasakal, Burak y Emre Sumer. "Gender recognition using innovative pattern recognition techniques". En 2018 26th Signal Processing and Communications Applications Conference (SIU). IEEE, 2018. http://dx.doi.org/10.1109/siu.2018.8404306.
Texto completoSlack, Marc G. "Autonomous navigation of mobile robots for real-world applications". En Applied Imaging Pattern Recognition, editado por Jane Harmon. SPIE, 1993. http://dx.doi.org/10.1117/12.142786.
Texto completoLiu, Ying. "Pattern recognition using Hilbert space". En Applications in Optical Science and Engineering, editado por David P. Casasent. SPIE, 1992. http://dx.doi.org/10.1117/12.131517.
Texto completoSchmalz, Mark S., Gerhard X. Ritter, Eric Hayden y Gary Key. "Algorithms for adaptive nonlinear pattern recognition". En SPIE Optical Engineering + Applications, editado por Mark S. Schmalz, Gerhard X. Ritter, Junior Barrera y Jaakko T. Astola. SPIE, 2011. http://dx.doi.org/10.1117/12.896561.
Texto completoHill, Robert E., Donald K. Fronek, Calton S. Faller y Richard A. Lane. "Pattern Recognition Utilizing Binary Light Modulators". En Spatial Light Modulators and Applications. Washington, D.C.: Optica Publishing Group, 1988. http://dx.doi.org/10.1364/slma.1988.the3.
Texto completoAguilar-González, Pablo Mario y Vitaly Kober. "Pattern recognition of an implicitly given target". En Optical Engineering + Applications, editado por Andrew G. Tescher. SPIE, 2008. http://dx.doi.org/10.1117/12.793912.
Texto completoInformes sobre el tema "Pattern recognition applications"
Howell, J. A., G. W. Eccleston, R. Whiteson, H. O. Menlove, C. C. Fuyat, J. K. Halbig, S. F. Klosterbuer y M. F. Mullen. Safeguards applications of pattern recognition and neural networks. Office of Scientific and Technical Information (OSTI), septiembre de 1993. http://dx.doi.org/10.2172/10102590.
Texto completoVarastehpour, Soheil, Hamid Sharifzadeh, Iman Ardekani y Abdolhossein Sarrafzadeh. Human Biometric Traits: A Systematic Review Focusing on Vascular Patterns. Unitec ePress, diciembre de 2020. http://dx.doi.org/10.34074/ocds.086.
Texto completoRohatgi, Upendra y Michael Furey. Development of Application of Pattern Recognition System. Office of Scientific and Technical Information (OSTI), marzo de 2010. http://dx.doi.org/10.2172/1012395.
Texto completoMarkova, Oksana, Serhiy Semerikov y Maiia Popel. СoCalc as a Learning Tool for Neural Network Simulation in the Special Course “Foundations of Mathematic Informatics”. Sun SITE Central Europe, mayo de 2018. http://dx.doi.org/10.31812/0564/2250.
Texto completoFoster, Thomas. Application of Pattern Recognition Techniques for Early Warning Radar (EWR) Discrimination. Fort Belvoir, VA: Defense Technical Information Center, enero de 1995. http://dx.doi.org/10.21236/ada298895.
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