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Chemometrics For Pattern Recognition

Author: Richard G. Brereton
Publisher: John Wiley & Sons
ISBN: 9780470746479
Size: 70.32 MB
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Over the past decade, pattern recognition has been one of the fastest growth points in chemometrics. This has been catalysed by the increase in capabilities of automated instruments such as LCMS, GCMS, and NMR, to name a few, to obtain large quantities of data, and, in parallel, the significant growth in applications especially in biomedical analytical chemical measurements of extracts from humans and animals, together with the increased capabilities of desktop computing. The interpretation of such multivariate datasets has required the application and development of new chemometric techniques such as pattern recognition, the focus of this work. Included within the text are: ‘Real world’ pattern recognition case studies from a wide variety of sources including biology, medicine, materials, pharmaceuticals, food, forensics and environmental science; Discussions of methods, many of which are also common in biology, biological analytical chemistry and machine learning; Common tools such as Partial Least Squares and Principal Components Analysis, as well as those that are rarely used in chemometrics such as Self Organising Maps and Support Vector Machines; Representation in full colour; Validation of models and hypothesis testing, and the underlying motivation of the methods, including how to avoid some common pitfalls. Relevant to active chemometricians and analytical scientists in industry, academia and government establishments as well as those involved in applying statistics and computational pattern recognition.

Machine Learning And Data Mining In Pattern Recognition

Author: Petra Perner
Publisher: Springer
ISBN: 3540480978
Size: 36.81 MB
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The field of machine learning and data mining in connection with pattern recognition enjoys growing popularity and attracts many researchers. Automatic pattern recognition systems have proven successful in many applications. The wide use of these systems depends on their ability to adapt to changing environmental conditions and to deal with new objects. This requires learning capabilities on the parts of these systems. The exceptional attraction of learning in pattern recognition lies in the specific data themselves and the different stages at which they get processed in a pattern recognition system. This results a specific branch within the field of machine learning. At the workshop, were presented machine learning approaches for image pre-processing, image segmentation, recognition and interpretation. Machine learning systems were shown on applications such as document analysis and medical image analysis. Many databases are developed that contain multimedia sources such as images, measurement protocols, and text documents. Such systems should be able to retrieve these sources by content. That requires specific retrieval and indexing strategies for images and signals. Higher quality database contents can be achieved if it were possible to mine these databases for their underlying information. Such mining techniques have to consider the specific characteristic of the image sources. The field of mining multimedia databases is just starting out. We hope that our workshop can attract many other researchers to this subject.

Neural Networks For Pattern Recognition

Author: Albert Nigrin
Publisher: MIT Press
ISBN: 9780262140546
Size: 18.38 MB
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In a simple and accessible way it extends embedding field theory into areas of machine intelligence that have not been clearly dealt with before.

Pattern Recognition

Author: Sergios Theodoridis
Publisher: Academic Press
ISBN: 9780080949123
Size: 69.27 MB
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This book considers classical and current theory and practice, of supervised, unsupervised and semi-supervised pattern recognition, to build a complete background for professionals and students of engineering. The authors, leading experts in the field of pattern recognition, have provided an up-to-date, self-contained volume encapsulating this wide spectrum of information. The very latest methods are incorporated in this edition: semi-supervised learning, combining clustering algorithms, and relevance feedback. · Thoroughly developed to include many more worked examples to give greater understanding of the various methods and techniques · Many more diagrams included--now in two color--to provide greater insight through visual presentation · Matlab code of the most common methods are given at the end of each chapter. · More Matlab code is available, together with an accompanying manual, via this site · Latest hot topics included to further the reference value of the text including non-linear dimensionality reduction techniques, relevance feedback, semi-supervised learning, spectral clustering, combining clustering algorithms. · An accompanying book with Matlab code of the most common methods and algorithms in the book, together with a descriptive summary, and solved examples including real-life data sets in imaging, and audio recognition. The companion book will be available separately or at a special packaged price (ISBN: 9780123744869). Thoroughly developed to include many more worked examples to give greater understanding of the various methods and techniques Many more diagrams included--now in two color--to provide greater insight through visual presentation Matlab code of the most common methods are given at the end of each chapter An accompanying book with Matlab code of the most common methods and algorithms in the book, together with a descriptive summary and solved examples, and including real-life data sets in imaging and audio recognition. The companion book is available separately or at a special packaged price (Book ISBN: 9780123744869. Package ISBN: 9780123744913) Latest hot topics included to further the reference value of the text including non-linear dimensionality reduction techniques, relevance feedback, semi-supervised learning, spectral clustering, combining clustering algorithms Solutions manual, powerpoint slides, and additional resources are available to faculty using the text for their course. Register at www.textbooks.elsevier.com and search on "Theodoridis" to access resources for instructor.

Pattern Recognition

Author: William Gibson
Publisher: Penguin UK
ISBN: 0141904461
Size: 77.42 MB
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Pattern Recognition - a pulsating techno-thriller by William Gibson, bestselling author of Neuromancer Cayce Pollard has been flown to London. She's a 'coolhunter' - her services for hire to global corporations desperate for certainty in a capricious and uncertain world. Now she's been offered a special project: track down the makers of the addictive online film that's lighting up the 'net. Hunting the source will take her to Tokyo and Moscow and put her in the sights of Japanese computer crazies and Russian Mafia men. She's up against those who want to control the film, to own it - who figure breaking the law is just another business strategy. The kind of people who relish turning the hunter into the hunted . . . William Gibson is a prophet and a satirist, a black comedian and an outstanding architect of cool. Readers of Neal Stephenson, Ray Bradbury and Iain M. Banks will love this book. Pattern Recognition is the first novel in the Blue Ant trilogy - read Spook Country and Zero History for more. 'A big novel, full of bold ideas . . . races along like an expert thriller' GQ 'Dangerously hip. Its dialogue and characterization will amaze you. A wonderfully detailed, reckless journey of espionage and lies' USA Today 'A compelling, humane story with a sympathetic heroine searching for meaning and consolation in a post-everything world' Daily Telegraph Idoru is a gripping techno-thriller by William Gibson, bestselling author of Neuromancer 'Fast, witty and cleverly politicized' Guardian

Image Processing And Pattern Recognition

Author: Cornelius T. Leondes
Publisher: Elsevier
ISBN: 9780080551449
Size: 51.41 MB
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Image Processing and Pattern Recognition covers major applications in the field, including optical character recognition, speech classification, medical imaging, paper currency recognition, classification reliability techniques, and sensor technology. The text emphasizes algorithms and architectures for achieving practical and effective systems, and presents many examples. Practitioners, researchers, and students in computer science, electrical engineering, andradiology, as well as those working at financial institutions, will value this unique and authoritative reference to diverse applications methodologies. Coverage includes: Optical character recognition Speech classification Medical imaging Paper currency recognition Classification reliability techniques Sensor technology Algorithms and architectures for achieving practical and effective systems are emphasized, with many examples illustrating the text. Practitioners, researchers, and students in computer science, electrical engineering, and radiology, as wellk as those working at financial institutions, will find this volume a unique and comprehensive reference source for this diverse applications area.

Pattern Recognition In Biology

Author: Marsha S. Corrigan
Publisher: Nova Publishers
ISBN: 9781600217166
Size: 80.99 MB
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Pattern recognition is the research area that studies the operation and design of systems that recognise patterns in data. It encloses subdisciplines like discriminant analysis, feature extraction, error estimation, cluster analysis, grammatical inference and parsing. This book presents research from around the world.

Pattern Recognition And Neural Networks

Author: Brian D. Ripley
Publisher: Cambridge University Press
ISBN: 9780521717700
Size: 79.74 MB
Format: PDF
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Ripley brings together two crucial ideas in pattern recognition: statistical methods and machine learning via neural networks. He brings unifying principles to the fore, and reviews the state of the subject. Ripley also includes many examples to illustrate real problems in pattern recognition and how to overcome them.