Download or read book Pattern Recognition written by Rjean Plamondon and published by World Scientific. This book was released on 1991 with total page 404 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book contains 15 reviewed papers selected from among those presented at the 4th Vision Interface Conference in Halifax, Canada 14 - 18 May 1990. The papers are grouped into three sections which deal with parallel architectures and neural networks, algorithms for analysis and processing, and systems and applications.
Download or read book Pattern Recognition Architectures Algorithms And Applications written by Rejean Plamondon and published by World Scientific. This book was released on 1991-08-12 with total page 404 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book contains 15 reviewed papers selected from among those presented at the 4th Vision Interface Conference in Halifax, Canada 14 - 18 May 1990. The papers are grouped into three sections which deal with parallel architectures and neural networks, algorithms for analysis and processing, and systems and applications.
Download or read book Artificial Neural Networks in Pattern Recognition written by Luca Pancioni and published by Springer. This book was released on 2018-08-29 with total page 415 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 8th IAPR TC3 International Workshop on Artificial Neural Networks in Pattern Recognition, ANNPR 2018, held in Siena, Italy, in September 2018. The 29 revised full papers presented together with 2 invited papers were carefully reviewed and selected from 35 submissions. The papers present and discuss the latest research in all areas of neural network- and machine learning-based pattern recognition. They are organized in two sections: learning algorithms and architectures, and applications. Chapter "Bounded Rational Decision-Making with Adaptive Neural Network Priors" is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.
Download or read book Artificial Neural Networks in Pattern Recognition written by Frank-Peter Schilling and published by Springer Nature. This book was released on 2020-09-01 with total page 313 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 9th IAPR TC3 International Workshop on Artificial Neural Networks in Pattern Recognition, ANNPR 2020, held in Winterthur, Switzerland, in September 2020. The conference was held virtually due to the COVID-19 pandemic. The 22 revised full papers presented were carefully reviewed and selected from 34 submissions. The papers present and discuss the latest research in all areas of neural network-and machine learning-based pattern recognition. They are organized in two sections: learning algorithms and architectures, and applications.
Download or read book Neural Networks in Pattern Recognition and Their Applications written by Chi-hau Chen and published by World Scientific. This book was released on 1991 with total page 176 pages. Available in PDF, EPUB and Kindle. Book excerpt: The revitalization of neural network research in the past few years has already had a great impact on research and development in pattern recognition and artificial intelligence. Although neural network functions are not limited to pattern recognition, there is no doubt that a renewed progress in pattern recognition and its applications now critically depends on neural networks. This volume specially brings together outstanding original research papers in the area and aims to help the continued progress in pattern recognition and its applications.
Download or read book Machine Learning Algorithms and Applications written by Mettu Srinivas and published by John Wiley & Sons. This book was released on 2021-08-10 with total page 372 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine Learning Algorithms is for current and ambitious machine learning specialists looking to implement solutions to real-world machine learning problems. It talks entirely about the various applications of machine and deep learning techniques, with each chapter dealing with a novel approach of machine learning architecture for a specific application, and then compares the results with previous algorithms. The book discusses many methods based in different fields, including statistics, pattern recognition, neural networks, artificial intelligence, sentiment analysis, control, and data mining, in order to present a unified treatment of machine learning problems and solutions. All learning algorithms are explained so that the user can easily move from the equations in the book to a computer program.
Download or read book Computational Intelligence for Pattern Recognition written by Witold Pedrycz and published by Springer. This book was released on 2018-04-30 with total page 431 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book presents a comprehensive and up-to-date review of fuzzy pattern recognition. It carefully discusses a range of methodological and algorithmic issues, as well as implementations and case studies, and identifies the best design practices, assesses business models and practices of pattern recognition in real-world applications in industry, health care, administration, and business. Since the inception of fuzzy sets, fuzzy pattern recognition with its methodology, algorithms, and applications, has offered new insights into the principles and practice of pattern classification. Computational intelligence (CI) establishes a comprehensive framework aimed at fostering the paradigm of pattern recognition. The collection of contributions included in this book offers a representative overview of the advances in the area, with timely, in-depth and comprehensive material on the conceptually appealing and practically sound methodology and practices of CI-based pattern recognition.
Download or read book Handbook of Pattern Recognition Computer Vision written by Chi-hau Chen and published by World Scientific. This book was released on 1999 with total page 1045 pages. Available in PDF, EPUB and Kindle. Book excerpt: Annotation. Presents the latest research findings in theory, techniques, algorithms, and major applications of pattern recognition and computer vision, as well as new hardware and architecture aspects. Contains sections on basic methods in pattern recognition and computer vision, nine recognition applications, inspection and robotic applications, and architectures and technology. Some areas discussed include cluster analysis, 3D vision of dynamic objects, speech recognition, computer vision in food handling, and video content analysis and retrieval. This second edition is extensively revised to describe progress in the field since 1993. Chen is affiliated with the electrical and computer engineering department at the University of Massachusetts-Dartmouth. Annotation copyrighted by Book News, Inc., Portland, OR.
Download or read book Binary Neural Networks written by Baochang Zhang and published by CRC Press. This book was released on 2023-12-13 with total page 218 pages. Available in PDF, EPUB and Kindle. Book excerpt: Deep learning has achieved impressive results in image classification, computer vision, and natural language processing. To achieve better performance, deeper and wider networks have been designed, which increase the demand for computational resources. The number of floatingpoint operations (FLOPs) has increased dramatically with larger networks, and this has become an obstacle for convolutional neural networks (CNNs) being developed for mobile and embedded devices. In this context, Binary Neural Networks: Algorithms, Architectures, and Applications will focus on CNN compression and acceleration, which are important for the research community. We will describe numerous methods, including parameter quantization, network pruning, low-rank decomposition, and knowledge distillation. More recently, to reduce the burden of handcrafted architecture design, neural architecture search (NAS) has been used to automatically build neural networks by searching over a vast architecture space. Our book will also introduce NAS and binary NAS and its superiority and state-of-the-art performance in various applications, such as image classification and object detection. We also describe extensive applications of compressed deep models on image classification, speech recognition, object detection, and tracking. These topics can help researchers better understand the usefulness and the potential of network compression on practical applications. Moreover, interested readers should have basic knowledge of machine learning and deep learning to better understand the methods described in this book. Key Features Reviews recent advances in CNN compression and acceleration Elaborates recent advances on binary neural network (BNN) technologies Introduces applications of BNN in image classification, speech recognition, object detection, and more
Download or read book Deep Learning Applications written by M. Arif Wani and published by Springer Nature. This book was released on 2020-02-28 with total page 184 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a compilation of selected papers from the 17th IEEE International Conference on Machine Learning and Applications (IEEE ICMLA 2018), focusing on use of deep learning technology in application like game playing, medical applications, video analytics, regression/classification, object detection/recognition and robotic control in industrial environments. It highlights novel ways of using deep neural networks to solve real-world problems, and also offers insights into deep learning architectures and algorithms, making it an essential reference guide for academic researchers, professionals, software engineers in industry, and innovative product developers.
Download or read book Fundamentals of Neural Networks written by Fausett and published by Prentice Hall. This book was released on 1994 with total page 300 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Pattern Recognition written by Wladyslaw Homenda and published by John Wiley & Sons. This book was released on 2018-03-07 with total page 256 pages. Available in PDF, EPUB and Kindle. Book excerpt: A new approach to the issue of data quality in pattern recognition Detailing foundational concepts before introducing more complex methodologies and algorithms, this book is a self-contained manual for advanced data analysis and data mining. Top-down organization presents detailed applications only after methodological issues have been mastered, and step-by-step instructions help ensure successful implementation of new processes. By positioning data quality as a factor to be dealt with rather than overcome, the framework provided serves as a valuable, versatile tool in the analysis arsenal. For decades, practical need has inspired intense theoretical and applied research into pattern recognition for numerous and diverse applications. Throughout, the limiting factor and perpetual problem has been data—its sheer diversity, abundance, and variable quality presents the central challenge to pattern recognition innovation. Pattern Recognition: A Quality of Data Perspective repositions that challenge from a hurdle to a given, and presents a new framework for comprehensive data analysis that is designed specifically to accommodate problem data. Designed as both a practical manual and a discussion about the most useful elements of pattern recognition innovation, this book: Details fundamental pattern recognition concepts, including feature space construction, classifiers, rejection, and evaluation Provides a systematic examination of the concepts, design methodology, and algorithms involved in pattern recognition Includes numerous experiments, detailed schemes, and more advanced problems that reinforce complex concepts Acts as a self-contained primer toward advanced solutions, with detailed background and step-by-step processes Introduces the concept of granules and provides a framework for granular computing Pattern recognition plays a pivotal role in data analysis and data mining, fields which are themselves being applied in an expanding sphere of utility. By facing the data quality issue head-on, this book provides students, practitioners, and researchers with a clear way forward amidst the ever-expanding data supply.
Download or read book Optical Pattern Recognition written by and published by . This book was released on 2003 with total page 129 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Image Processing and Pattern Recognition written by Cornelius T. Leondes and published by Elsevier. This book was released on 1998-02-09 with total page 407 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Pattern Recognition with Neural Networks in C written by Abhijit S. Pandya and published by CRC Press. This book was released on 2020-10-12 with total page 434 pages. Available in PDF, EPUB and Kindle. Book excerpt: The addition of artificial neural network computing to traditional pattern recognition has given rise to a new, different, and more powerful methodology that is presented in this interesting book. This is a practical guide to the application of artificial neural networks. Geared toward the practitioner, Pattern Recognition with Neural Networks in C++ covers pattern classification and neural network approaches within the same framework. Through the book's presentation of underlying theory and numerous practical examples, readers gain an understanding that will allow them to make judicious design choices rendering neural application predictable and effective. The book provides an intuitive explanation of each method for each network paradigm. This discussion is supported by a rigorous mathematical approach where necessary. C++ has emerged as a rich and descriptive means by which concepts, models, or algorithms can be precisely described. For many of the neural network models discussed, C++ programs are presented for the actual implementation. Pictorial diagrams and in-depth discussions explain each topic. Necessary derivative steps for the mathematical models are included so that readers can incorporate new ideas into their programs as the field advances with new developments. For each approach, the authors clearly state the known theoretical results, the known tendencies of the approach, and their recommendations for getting the best results from the method. The material covered in the book is accessible to working engineers with little or no explicit background in neural networks. However, the material is presented in sufficient depth so that those with prior knowledge will find this book beneficial. Pattern Recognition with Neural Networks in C++ is also suitable for courses in neural networks at an advanced undergraduate or graduate level. This book is valuable for academic as well as practical research.
Download or read book Supervised and Unsupervised Pattern Recognition written by Evangelia Miche Tzanakou and published by CRC Press. This book was released on 2017-12-19 with total page 392 pages. Available in PDF, EPUB and Kindle. Book excerpt: There are many books on neural networks, some of which cover computational intelligence, but none that incorporate both feature extraction and computational intelligence, as Supervised and Unsupervised Pattern Recognition does. This volume describes the application of a novel, unsupervised pattern recognition scheme to the classification of various types of waveforms and images. This substantial collection of recent research begins with an introduction to Neural Networks, classifiers, and feature extraction methods. It then addresses unsupervised and fuzzy neural networks and their applications to handwritten character recognition and recognition of normal and abnormal visual evoked potentials. The third section deals with advanced neural network architectures-including modular design-and their applications to medicine and three-dimensional NN architecture simulating brain functions. The final section discusses general applications and simulations, such as the establishment of a brain-computer link, speaker identification, and face recognition. In the quickly changing field of computational intelligence, every discovery is significant. Supervised and Unsupervised Pattern Recognition gives you access to many notable findings in one convenient volume.
Download or read book Pattern Recognition with Fuzzy Objective Function Algorithms written by James C. Bezdek and published by Springer Science & Business Media. This book was released on 2013-03-13 with total page 267 pages. Available in PDF, EPUB and Kindle. Book excerpt: The fuzzy set was conceived as a result of an attempt to come to grips with the problem of pattern recognition in the context of imprecisely defined categories. In such cases, the belonging of an object to a class is a matter of degree, as is the question of whether or not a group of objects form a cluster. A pioneering application of the theory of fuzzy sets to cluster analysis was made in 1969 by Ruspini. It was not until 1973, however, when the appearance of the work by Dunn and Bezdek on the Fuzzy ISODATA (or fuzzy c-means) algorithms became a landmark in the theory of cluster analysis, that the relevance of the theory of fuzzy sets to cluster analysis and pattern recognition became clearly established. Since then, the theory of fuzzy clustering has developed rapidly and fruitfully, with the author of the present monograph contributing a major share of what we know today. In their seminal work, Bezdek and Dunn have introduced the basic idea of determining the fuzzy clusters by minimizing an appropriately defined functional, and have derived iterative algorithms for computing the membership functions for the clusters in question. The important issue of convergence of such algorithms has become much better understood as a result of recent work which is described in the monograph.
