Pattern Recognition in Industry

Author: Phiroz Bhagat
Publisher: Elsevier
ISBN: 9780080456027
Format: PDF, ePub
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"Find it hard to extract and utilise valuable knowledge from the ever-increasing data deluge?" If so, this book will help, as it explores pattern recognition technology and its concomitant role in extracting useful information to build technical and business models to gain competitive industrial advantage. *Based on first-hand experience in the practice of pattern recognition technology and its development and deployment for profitable application in Industry. Phiroz Bhagat is often referred to as the pioneer of neural net and pattern recognition technology, and is uniquely qualified to write this book. He brings more than two decades of experience in the "real-world" application of cutting-edge technology for competitive advantage in industry. Two wave fronts are upon us today: we are being bombarded by an enormous amount of data, and we are confronted by continually increasing technical and business advances. Ideally, the endless stream of data should be one of our major assets. However, this potential asset often tends to overwhelm rather than enrich. Competitive advantage depends on our ability to extract and utilize nuggets of valuable knowledge and insight from this data deluge. The challenges that need to be overcome include the under-utilization of available data due to competing priorities, and the separate and somewhat disparate existing data systems that have difficulty interacting with each other. Conventional approaches to formulating models are becoming progressively more expensive in time and effort. To impart a competitive edge, engineering science in the 21st century needs to augment traditional modelling processes by auto-classifying and self-organizing data; developing models directly from operating experience, and then optimizing the results to provide effective strategies and operating decisions. This approach has wide applicability; in areas ranging from manufacturing processes, product performance and scientific research, to financial and business fields. This monograph explores pattern recognition technology, and its concomitant role in extracting useful knowledge to build technical and business models directly from data, and in optimizing the results derived from these models within the context of delivering competitive industrial advantage. It is not intended to serve as a comprehensive reference source on the subject. Rather, it is based on first-hand experience in the practice of this technology: its development and deployment for profitable application in industry. The technical topics covered in the monograph will focus on the triad of technological areas that constitute the contemporary workhorses of successful industrial application of pattern recognition. These are: systems for self-organising data; data-driven modelling; and genetic algorithms as robust optimizers. "Find it hard to extract and utilise valuable knowledge from the ever-increasing data deluge?" If so, this book will help, as it explores pattern recognition technology and its concomitant role in extracting useful information to build technical and business models to gain competitive industrial advantage. Based on first-hand experience in the practice of pattern recognition technology and its development and deployment for profitable application in Industry. Phiroz Bhagat is often referred to as the pioneer of neural net and pattern recognition technology, and is uniquely qualified to write this book. He brings more than two decades of experience in the "real-world" application of cutting-edge technology for competitive advantage in industry.

Pattern Recognition Technologies and Applications Recent Advances

Author: Verma, Brijesh
Publisher: IGI Global
ISBN: 1599048094
Format: PDF, ePub, Docs
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The nature of handwriting in our society has significantly altered over the ages due to the introduction of new technologies such as computers and the World Wide Web. With increases in the amount of signature verification needs, state of the art internet and paper-based automated recognition methods are necessary. Pattern Recognition Technologies and Applications: Recent Advances provides cutting-edge pattern recognition techniques and applications. Written by world-renowned experts in their field, this easy to understand book is a must have for those seeking explanation in topics such as on- and offline handwriting and speech recognition, signature verification, and gender classification.

Image Processing for the Food Industry

Author: E. R. Davies
Publisher: World Scientific
ISBN: 9789810240226
Format: PDF, ePub, Docs
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This monograph provides detailed background on the image processing problems encountered in the food industry when automatic control and inspection systems are being designed and installed. It starts with a careful study of image processing and machine vision methodology, and then goes on to analyse how this can be applied in the main areas of food processing and production. A case study approach is used to give relevance to the work, making the book user-friendly. This book will help the food industry to observe 'due diligence', and researchers to be more aware of the problems of analysing images of food products.

Vein Pattern Recognition

Author: Chuck Wilson
Publisher: CRC Press
ISBN: 1439857563
Format: PDF, Kindle
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As one of the most promising biometric technologies, vein pattern recognition (VPR) is quickly taking root around the world and may soon dominate applications where people focus is key. Among the reasons for VPR’s growing acceptance and use: it is more accurate than many other biometric methods, it offers greater resistance to spoofing, it focuses on people and their privacy, and has few negative cultural connotations. Vein Pattern Recognition: A Privacy-Enhancing Biometric provides a comprehensive and practical look at biometrics in general and at vein pattern recognition specifically. It discusses the emergence of this reliable but underutilized technology and evaluates its capabilities and benefits. The author, Chuck Wilson, an industry veteran with more than 25 years of experience in the biometric and electronic security fields, examines current and emerging VPR technology along with the myriad applications of this dynamic technology. Wilson explains the use of VPR and provides an objective comparison of the different biometric methods in use today—including fingerprint, eye, face, voice recognition, and dynamic signature verification. Highlighting current VPR implementations, including its widespread acceptance and use for identity verification in the Japanese banking industry, the text provides a complete examination of how VPR can be used to protect sensitive information and secure critical facilities. Complete with best-practice techniques, the book supplies invaluable guidance on selecting the right combination of biometric technologies for specific applications and on properly implementing VPR as part of an overall security system.

Handbook of Pattern Recognition and Computer Vision 5th Edition

Author: Chi-hau Chen
Publisher: World Scientific
ISBN: 9814656534
Format: PDF, Docs
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The book provides an up-to-date and authoritative treatment of pattern recognition and computer vision, with chapters written by leaders in the field. On the basic methods in pattern recognition and computer vision, topics range from statistical pattern recognition to array grammars to projective geometry to skeletonization, and shape and texture measures. Recognition applications include character recognition and document analysis, detection of digital mammograms, remote sensing image fusion, and analysis of functional magnetic resonance imaging data, etc.

Pattern Recognition and Machine Learning

Author: Christopher M. Bishop
Publisher: Springer
ISBN: 9781493938438
Format: PDF, ePub, Mobi
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This is the first textbook on pattern recognition to present the Bayesian viewpoint. The book presents approximate inference algorithms that permit fast approximate answers in situations where exact answers are not feasible. It uses graphical models to describe probability distributions when no other books apply graphical models to machine learning. No previous knowledge of pattern recognition or machine learning concepts is assumed. Familiarity with multivariate calculus and basic linear algebra is required, and some experience in the use of probabilities would be helpful though not essential as the book includes a self-contained introduction to basic probability theory.

Handbook Of Pattern Recognition And Computer Vision

Author: Wang Patrick S P
Publisher: World Scientific
ISBN: 9814505218
Format: PDF, ePub
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Pattern recognition and computer vision and their applications have experienced enormous progress in research and development over the last two decades. This comprehensive handbook, with chapters by leading experts in their fields, documents both the basics and new and advanced results.The book gives the most total treatment of basic methods in pattern recognition including statistical, neurocomputing, syntactic/structural/grammatical approaches, feature selection and cluster analysis; and an extensive presentation of basic methods in computer vision including texture analysis and models, color, geometrical tools, image sequence analysis, etc. Major and unique applications are also covered, such as food handling using computer vision, non-destructive evaluation of materials, applications in economics and business, medical image recognition and understanding, etc. Broader system aspects are also examined, including optical pattern recognition and architectures for computer vision.Researchers, students and users of pattern recognition and computer vision will find the book an essential reference tool. The volume is also an invaluable collection of basic techniques and principles, which would otherwise be hard to assemble, in one convenient volume.

Machine Learning and Data Mining in Pattern Recognition

Author: Petra Perner
Publisher: Springer
ISBN: 3319624164
Format: PDF, Kindle
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This book constitutes the refereed proceedings of the 13th International Conference on Machine Learning and Data Mining in Pattern Recognition, MLDM 2017, held in New York, NY, USA in July/August 2017.The 31 full papers presented in this book were carefully reviewed and selected from 150 submissions. The topics range from theoretical topics for classification, clustering, association rule and pattern mining to specific data mining methods for the different multi-media data types such as image mining, text mining, video mining, and Web mining.

Progress in Pattern Recognition Image Analysis and Applications

Author: José Francisco Martínez-Trinidad
Publisher: Springer Science & Business Media
ISBN: 3540465561
Format: PDF, Docs
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This book constitutes the refereed proceedings of the 11th Iberoamerican Congress on Pattern Recognition, CIARP 2006, held in Cancun, Mexico in November 2006. The 99 revised full papers presented together with three keynote articles were carefully reviewed and selected from 239 submissions. The papers cover ongoing research and mathematical methods.