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Author : Bernd Jochen Kurz
Publisher : 1969 [c1972]
Page : 224 pages
File Size : 38,51 MB
Release : 1969
Category : Optical pattern recognition
ISBN :
Author : Bernd Jochen Kurz
Publisher :
Page : 112 pages
File Size : 42,14 MB
Release : 1971
Category : Optical pattern recognition
ISBN :
Author : Thomas Lu
Publisher :
Page : 205 pages
File Size : 26,62 MB
Release : 2018-11-16
Category : Machine learning
ISBN : 9781536144291
Artificial Intelligence (AI) has become a popular research topic recently. Pattern recognition (PR) is an important part of an AI system. If the AI is considered as the digital brain, then the PR is the visual and auditory cortex that converts the optical signals from the eyes and the acoustic signals from the ears to meaningful symbolic texts that the brain can digest. Over the past 40+ years, the processing speed of a digital computer has increased from kbits/s to tera floating point operations per second (TFLOPS), a 109 times acceleration. PR research has made significant advancements along the advancement of digital hardware, especially the graphical processing unit (GPU) technology that helps the rapid processing of complex images. In this book, the authors have collected the latest work from leading researchers in the PR fields. The topics are broad, which include optical implementation of various filters, digital implementation of state-of-the-art neural network (NN) training methods, and the latest deep leaning (DL) models. We also included applications of PR in various fields.
Author : Eileen C. Schwab
Publisher : Elsevier
Page : 260 pages
File Size : 45,69 MB
Release : 2013-09-11
Category : Reference
ISBN : 1483259617
Pattern Recognition by Humans and Machines, Volume 2: Visual Perception provides information pertinent to the fundamental aspects of research on perception. This book focuses on several fundamental problems of pattern recognition in speech perception and visual form perception. Organized into seven chapters, this volume begins with an overview of some of the basic theoretical questions in speech perception. This text then explores the spatiotemporal orchestration of visuosensory attentional and oculomotor processes involved in active visual exploration. Other chapters consider several basic questions concerning visual form perception, including the perception of patterns and features. This book discusses as well the role of eye movements in pattern processing and models of segmentation and pattern recognition. The final chapter describes the distinctions made in perceptual processing between model-driven and data-driven processing. This book is a valuable resource for psychologists in general and specialists in the field of perception. Computer and cognitive scientists will also find this book useful.
Author : Bruce G. Batchelor
Publisher : Springer Science & Business Media
Page : 486 pages
File Size : 41,91 MB
Release : 2012-12-06
Category : Computers
ISBN : 146134154X
Pattern recognition is a child of modern technology; electronics and computers in particular have inspired research and made it possible to develop the subject in a way which would have been impossible otherwise. It is a rapidly growing research field which began to flourish in the 1960s and which is beginning to produce commercial devices. Significant developments have been made, both in the theory and practical engineering of the subject, but there is evidence of a schism developing between these two approaches. Practical machines have usually been designed on an ad hoc basis, with little use being made of advanced theory. It is difficult to provide a rigorous mathematical treatment of many problems pertinent to a practical situation. This is due, in part at least, to a conceptual rift between theory and practice. The mathematics of optimal systems is well developed, whereas pragmatists are more concerned with vaguer ideas of reasonable and sufficient. In some situations, the quest for optimality can constrain research and retard practical progress. This can occur, for example, if too narrow a view is taken of "optimal": the accuracy of a system may be optimal whereas its speed, cost, or physical size may be grossly suboptimal. The objective of this book is to present a glimpse of the pragmatic approach to pattern recognition; there already exist a number of excellent texts describing theoretical developments.
Author : C. H. Chen
Publisher : World Scientific
Page : 1045 pages
File Size : 37,10 MB
Release : 1999
Category : Computers
ISBN : 9812384731
The very significant advances in computer vision and pattern recognition and their applications in the last few years reflect the strong and growing interest in the field as well as the many opportunities and challenges it offers. The second edition of this handbook represents both the latest progress and updated knowledge in this dynamic field. The applications and technological issues are particularly emphasized in this edition to reflect the wide applicability of the field in many practical problems. To keep the book in a single volume, it is not possible to retain all chapters of the first edition. However, the chapters of both editions are well written for permanent reference.
Author : Blom Marleah
Publisher : World Scientific
Page : 300 pages
File Size : 17,62 MB
Release : 2019-06-17
Category : Computers
ISBN : 9811203539
The fifth volume in this book series consists of a collection of new papers written by a diverse group of international scholars. Papers and presentations were carefully selected from 160 papers submitted to the International Conference on Pattern Recognition and Artificial Intelligence held in Montreal, Quebec (May 2018) and an associated free public lecture entitled 'Artificial Intelligence and Pattern Recognition: Trendy Technologies in Our Modern Digital World'. Chapters address topics such as the evolution of AI, natural language processing, off and on-line handwriting analysis, tracking and detection systems, neural networks, rating video games, computer-aided diagnosis, and digital learning.Within an increasingly digital world, 'artificial intelligence' is becoming a household term and a topic of great interest to many people worldwide. Pattern recognition, in using key features to classify data, has a strong relationship with artificial intelligence. This book not only complements other monographs in the series, it also provides the latest information. It is geared to promote interest and understanding about pattern recognition and artificial intelligence to the general public. It may also be of interest to graduate students and researchers in the field. Rather than focusing on one specific area, the book introduces readers to various basic concepts and to various potential areas where pattern recognition and artificial intelligence can be applied to make valuable contributions to other fields such as medicine, teaching and learning, forensic science, surveillance, online reviews, computer vision and object tracking.
Author : K. S. Fu
Publisher : Springer Science & Business Media
Page : 248 pages
File Size : 35,98 MB
Release : 2013-03-07
Category : Computers
ISBN : 3642677401
Since its publication in 1976, the original volume has been warmly received. We have decided to put out this updated paperback edition so that the book can be more accessible to students. This paperback edition is essentially the same as the original hardcover volume except for the addition of a new chapter (Chapter 7) which reviews the recent advances in pattern recognition and image processing. Because of the limitations of length, we can only report the highlights and point the readers to the literature. A few typographical errors in the original edition were corrected. We are grateful to the National Science Foundation and the Office of Naval Research for supporting the editing of this book as well as the work described in Chapter 4 and a part of Chapter 7. West Lafayette, Indiana March 1980 K. S. Fu Preface to the First Edition During the past fifteen years there has been a considerable growth of interest in problems of pattern recognition. Contributions to the blossom of this area have come from many disciplines, including statistics, psychology, linguistics, computer science, biology, taxonomy, switching theory, communication theory, control theory, and operations research. Many different approaches have been proposed and a number of books have been published. Most books published so far deal with the decision-theoretic (or statistical) approach or the syntactic (or linguistic) is still far from its maturity, many approach.
Author : Paul Fieguth
Publisher : Springer
Page : 0 pages
File Size : 49,10 MB
Release : 2022-11-10
Category : Technology & Engineering
ISBN : 9783030959937
The domains of Pattern Recognition and Machine Learning have experienced exceptional interest and growth, however the overwhelming number of methods and applications can make the fields seem bewildering. This text offers an accessible and conceptually rich introduction, a solid mathematical development emphasizing simplicity and intuition. Students beginning to explore pattern recognition do not need a suite of mathematically advanced methods or complicated computational libraries to understand and appreciate pattern recognition; rather the fundamental concepts and insights, eminently teachable at the undergraduate level, motivate this text. This book provides methods of analysis that the reader can realistically undertake on their own, supported by real-world examples, case-studies, and worked numerical / computational studies.
Author : Sergios Theodoridis
Publisher : Academic Press
Page : 233 pages
File Size : 15,52 MB
Release : 2010-03-03
Category : Computers
ISBN : 0080922759
Introduction to Pattern Recognition: A Matlab Approach is an accompanying manual to Theodoridis/Koutroumbas' Pattern Recognition. It includes 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. This text is designed for electronic engineering, computer science, computer engineering, biomedical engineering and applied mathematics students taking graduate courses on pattern recognition and machine learning as well as R&D engineers and university researchers in image and signal processing/analyisis, and computer vision. Matlab code and descriptive summary of the most common methods and algorithms in Theodoridis/Koutroumbas, Pattern Recognition, Fourth Edition Solved examples in Matlab, including real-life data sets in imaging and audio recognition Available separately or at a special package price with the main text (ISBN for package: 978-0-12-374491-3)