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Pattern Recognition. From FOLDOC. "A branch of artificial intelligence concerned with the classification or description of observations. Pattern recognition aims to classify data (patterns) based on either a priori knowledge or on statistical information extracted from the patterns. The patterns to be classified are usually groups of measurements or observations, defining points in an appropriate multidimensional space." How Do Post Office Machines Read Addresses? By Ben Mauk. LiveScience.com (August 16, 2007). "The United States Postal Service (USPS) began researching remote computer readers (RCRs) for handwritten addresses in 1983. At the time, the technology required to scan and understand a human scrawl simply did not exist. Not until Christmas of 1997 did the USPS and the University of Buffalo's Center for Excellence in Document Analysis and Recognition (CEDAR) deploy its first handwritten address-reading prototype.... Humans read and comprehend with an ease that belies the immense difficulty of computer pattern recognition (including patterns such as numbers and letters). It is one of the central problems in artificial intelligence. ... 'That Christmas alone we saved several thousand dollars for the post office,' Sargur Srihari told LiveScience. Srihari founded CEDAR and led the early research on large-scale RCRs. Today, the large majority of letters sent through the post office are read and sorted entirely by computer. According to Srihari, current reading success rates are above 90 percent."
The Pattern Recognition Files. A very comprehensive collection of pattern recognition resources from the Pattern Recognition Group at Delft University of Technology. Maintained by Bob Duin.
FVC2002: the Second International Fingerprint Verification Competition. Sponsored by the Biometric Systems Lab at the University of Bologna, the Pattern Recognition and Image Processing Laboratory at Michigan State University, and the U.S. National Biometric Test Center at San Jose State University.
BiometricsResearch. From the Pattern Recognitionand Image Processing Lab, Department of Computer Science andEngineering, Michigan State University. "Biometrics refers to the automaticidentification of a person based on his/her physiological orbehavioral characteristics. ... Various types of biometric systemsare being used for real-time identification, the most popularare based on face recognition and fingerprint matching. However,there are other biometric systems that utilize iris and retinalscan, speech, facial thermograms, and hand geometry. A biometricsystem is essentially a pattern recognition system which makesa personal identification by determining the authenticity ofa specific physiological or behavioral characteristic possessedby the user."
Computer programs help flag insurance fraud before payment. By Julie Appleby. USA Today (November 7, 2006). "Computer sleuths trying to stop health care fraud say they have a new weapon: computer programs that can flag potential fraud even before medical claims are paid. ... Insurer Aetna says its new computer software helped it stop $89 million in payments before they reached medical providers last year. That compares with the $15 million in fraud repayments it was able to collect after the fact. ... While the software systems may differ, their main effort is to spot medical providers who vary from the norm. 'Pattern recognition is a growing field in health fraud detection,' says Malcolm Sparrow, a professor at Harvard's John F. Kennedy School of Government and author of License to Steal: How Fraud Bleeds America's Health Care System." The Neural Approach to Pattern Recognition. Artificial neural networks could surpass the capabilities of conventional computer-based pattern recognition systems. By John Peter Jesan. Ubiquity (April 14 - 20, 2004; Volume 5, Issue 7). "For example, when we see a dog, first we recognize that it's an animal....This recognition concept is simple and familiar to everybody in the real world environment, but in the world of artificial intelligence, recognizing such objects is an amazing feat. The functionality of the human brain is amazing; it is not comparable with any artificial machines or software. Let us go deeper and analyze what is recognition and how it is done through machines. ... In this article, I am concerned with recognition of concrete items. Applications include finger print identification, voice recognition, face recognition, character recognition, signature recognition and classification of objects in scientific/research areas such as astronomy, engineering, statistics, medical, machine learning and neural networks." Bookish Math - Statistical tests are unraveling knotty literary mysteries. By Erica Klarreich. Science News (December 20, 2003; Vol. 164, No. 25). "Stylometry ['the science of measuring literary style'] is now entering a golden era. In the past 15 years, researchers have developed an arsenal of mathematical tools, from statistical tests to artificial intelligence techniques, for use in determining authorship. ... For decades, computers have supported the work of experts in stylometry. Now, computers are becoming experts in their own right, as some researchers apply artificial intelligence techniques to the question of authorship. ... Yet another analysis of the Federalist Papers was presented at a computer science conference in October. Glenn Fung of Siemens Medical Solutions in Malvern, Pa., used one of artificial intelligence's newest tools, a pattern-recognition technique called support-vector machines." Fingerprinting Plays Key Role in Biometrics Boom. By Paul Korzeniowski. TechNewsWorld (January 18, 2005). "Fingerprinting is an authentication technique that has helped law enforcement officials identify potential criminals for decades, but recently it has started to gain wider usage. The technique is emerging as the most popular form of biometrics, and much of the budding interest is coming from government agencies looking to enhance physical security, such as access to buildings. Corporations are also making a move toward using fingerprinting technology to provide more reliable identification of employees, business partners and customers. In 2004, fingerprinting accounted for US$367 million of the $1.2 billion biometric companies generated in worldwide revenue, according to market research firm International Biometric Group." GMU's Harry Wechsler. (October 31, 2005) "Technology Research News Editor Eric Smalley carried out an email conversation with Harry Wechsler, Professor of Computer Science and Director of the Distributed and Intelligent Computation Center at George Mason University. Wechsler's research centers around making computers more intelligent by giving them the ability to recognize patterns." The Pattern Recognition Basis of Artificial Intelligence. By Donald Tveter. IEEE Computer Society Press and John Wiley & Sons, Inc. (1998). "This textbook is unique in a number of ways. First, it pays extra attention to the new ideas in AI: neural networking, case based reasoning and memory based reasoning while including the important aspects of traditional symbol processing AI. ... There are additional online only chapters on More Neural Networking, More Prolog and Lisp, as well as neural networking software and an outline and commentary on the book [here] " International Journal of Pattern Recognition and Artificial Intelligence (IJPRAI) "This journal publishes both applications and theory-oriented articles on new developments in the fields of pattern recognition and artificial intelligence, and is of interest to both researchers in industry and academia. From the beginning, there has always been a close relationship between the disciplines of pattern recognition and artificial intelligence. The recognition and understanding of sensory data like speech or images, which are major concerns in pattern recognition, have always been considered as important subfields of artificial intelligence. On the other hand, topics like knowledge representation, inference, search or learning that belong to the center of artificial intelligence, have constantly attracted the attention of researchers working in pattern recognition. JPRAI is the first to cover both fields in one periodical, and particular emphasis is put on papers which are in the intersection of both fields." Pattern Recognition - The Journal of the Pattern Recognition Society, from Elsevier. "Original papers cover all methods, techniques and applications of pattern recognition, artificial intelligence, image processing, 2-D and 3-D matching, expert systems and robotics." Transactions on Pattern Analysis and Machine Intelligence (TPAMI) from IIIE "is published monthly. Its Editorial Board strives to publish papers that present important research results within PAMI's scope. These include statistical and structural pattern recognition; image analysis; computational models of vision; computer vision systems; enhancement, restoration, segmentation, feature extraction, shape and texture analysis; applications of pattern analysis in medicine, industry, government, and the arts and sciences; artificial intelligence, knowledge representation, logical and probabilistic inference, learning, speech recognition, character and text recognition, syntactic and semantic processing, understanding natural language, expert systems, and specialized architectures for such processing."
Center of Excellence for Document Analysis and Recognition (CEDAR). "Research at CEDAR focuses on the theory and application of pattern recognition, machine learning, and information retrieval. Over the years, the applications explored have included document analysis and recognition, forensic document examination, textual information retrieval, biometrics, medical informatics, and bio-informatics."
The Circuit Theory and Signal Processing Lab of the Faculte Polytechnique de Mons. "Our activities in Pattern Recognition are related to off-line hand-written character recognition (including document analysis and segmentation), manufacturing fault detection and classification, and texture analysis. Our topics of research also include real-time machine vision and license plates identification." ICPR2004 - The 17th International Conference on Pattern Recognition, sponsored by The International Association for Pattern Recognition. took place August 23-26, 2004 in Cambridge, UK. Be sure to check out the various workshops. Los Alamos National Laboratory Machine Learning & Pattern Recognition Team. "Our research is making fundamental advances in the field of computational learning theory, and we build on these results to develop robust solutions to a wide variety of real-world pattern recognition and anomaly detection problems." Pattern Recognition and Image Processing Lab. Department of Computer Science and Engineering, Michigan State University. "The Pattern Recognition and Image Processing (PRIP) Lab faculty and students investigate the use of machines to recognize patterns or objects. Methods are developed to sense objects, to discover which of their features distinguish them from others, and to design algorithms which can be used by a machine to do the classification. ... Important applications include face recognition, fingerprint identification, document image analysis, 3D object model construction, robot navigation, and visualization/exploration of 3D volumetric data. Current research problems include biometric authentication, automatic surveillance and tracking, handless HCI, face modeling, digital watermarking and analyzing structure of online documents. Recent graduates of the lab have worked on handwriting recognition, signature verification, visual learning, and image retrieval." |
