Hybrid Methods In Pattern Recognition PDF Download
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| Author | : Horst Bunke |
| Publisher | : World Scientific |
| Total Pages | : 338 |
| Release | : 2002-05-22 |
| Genre | : Computers |
| ISBN | : 9814489549 |
Download Hybrid Methods In Pattern Recognition Book in PDF, ePub and Kindle
The field of pattern recognition has seen enormous progress since its beginnings almost 50 years ago. A large number of different approaches have been proposed. Hybrid methods aim at combining the advantages of different paradigms within a single system.Hybrid Methods in Pattern Recognition is a collection of articles describing recent progress in this emerging field. It covers topics such as the combination of neural nets with fuzzy systems or hidden Markov models, neural networks for the processing of symbolic data structures, hybrid methods in data mining, the combination of symbolic and subsymbolic learning, and others. Also included is recent work on multiple classifier systems. Furthermore, the book deals with applications in on-line and off-line handwriting recognition, remotely sensed image interpretation, fingerprint identification, and automatic text categorization.
| Author | : Horst Bunke |
| Publisher | : World Scientific |
| Total Pages | : 338 |
| Release | : 2002 |
| Genre | : Technology & Engineering |
| ISBN | : 9810248326 |
Download Hybrid Methods in Pattern Recognition Book in PDF, ePub and Kindle
The field of pattern recognition has seen enormous progress since its beginnings almost 50 years ago. A large number of different approaches have been proposed. Hybrid methods aim at combining the advantages of different paradigms within a single system. Hybrid Methods in Pattern Recognition is a collection of articles describing recent progress in this emerging field. It covers topics such as the combination of neural nets with fuzzy systems or hidden Markov models, neural networks for the processing of symbolic data structures, hybrid methods in data mining, the combination of symbolic and subsymbolic learning, and so on. Also included is recent work on multiple classifier systems. Furthermore, the book deals with applications in on-line and off-line handwriting recognition, remotely sensed image interpretation, fingerprint identification, and automatic text categorization.
| Author | : Siddhartha Bhattacharyya |
| Publisher | : CRC Press |
| Total Pages | : 502 |
| Release | : 2017-10-30 |
| Genre | : Computers |
| ISBN | : 1351650203 |
Download Hybrid Intelligent Techniques for Pattern Analysis and Understanding Book in PDF, ePub and Kindle
Hybrid Intelligent Techniques for Pattern Analysis and Understanding outlines the latest research on the development and application of synergistic approaches to pattern analysis in real-world scenarios. An invaluable resource for lecturers, researchers, and graduates students in computer science and engineering, this book covers a diverse range of hybrid intelligent techniques, including image segmentation, character recognition, human behavioral analysis, hyperspectral data processing, and medical image analysis.
| Author | : Siddhartha Bhattacharyya |
| Publisher | : Academic Press |
| Total Pages | : 250 |
| Release | : 2020-03-05 |
| Genre | : Computers |
| ISBN | : 012818700X |
Download Hybrid Computational Intelligence Book in PDF, ePub and Kindle
Hybrid Computational Intelligence: Challenges and Utilities is a comprehensive resource that begins with the basics and main components of computational intelligence. It brings together many different aspects of the current research on HCI technologies, such as neural networks, support vector machines, fuzzy logic and evolutionary computation, while also covering a wide range of applications and implementation issues, from pattern recognition and system modeling, to intelligent control problems and biomedical applications. The book also explores the most widely used applications of hybrid computation as well as the history of their development. Each individual methodology provides hybrid systems with complementary reasoning and searching methods which allow the use of domain knowledge and empirical data to solve complex problems. Provides insights into the latest research trends in hybrid intelligent algorithms and architectures Focuses on the application of hybrid intelligent techniques for pattern mining and recognition, in big data analytics, and in human-computer interaction Features hybrid intelligent applications in biomedical engineering and healthcare informatics
| Author | : E.S. Gelsema |
| Publisher | : North Holland |
| Total Pages | : 600 |
| Release | : 1994-09-30 |
| Genre | : Computers |
| ISBN | : |
Download Pattern Recognition in Practice IV: Multiple Paradigms, Comparative Studies and Hybrid Systems Book in PDF, ePub and Kindle
These proceedings are divided into six sections: pattern recognition; signal and image processing; probabilistic reasoning; neural networks; comparative studies; and hybrid systems. They offer prospective users examples of a range of applications of the methods described.
| Author | : Sankar K. Pal |
| Publisher | : World Scientific |
| Total Pages | : 644 |
| Release | : 2001 |
| Genre | : Computers |
| ISBN | : 9789812386533 |
Download Pattern Recognition Book in PDF, ePub and Kindle
This volume, containing contributions by experts from all over the world, is a collection of 21 articles which present review and research material describing the evolution and recent developments of various pattern recognition methodologies, ranging from statistical, syntactic/linguistic, fuzzy-set-theoretic, neural, genetic-algorithmic and rough-set-theoretic to hybrid soft computing, with significant real-life applications. In addition, the book describes efficient soft machine learning algorithms for data mining and knowledge discovery. With a balanced mixture of theory, algorithms and applications, as well as up-to-date information and an extensive bibliography, Pattern Recognition: From Classical to Modern Approaches is a very useful resource. Contents: Pattern Recognition: Evolution of Methodologies and Data Mining (A Pal & S K Pal); Adaptive Stochastic Algorithms for Pattern Classification (M A L Thathachar & P S Sastry); Shape in Images (K V Mardia); Decision Trees for Classification: A Review and Some New Results (R Kothari & M Dong); Syntactic Pattern Recognition (A K Majumder & A K Ray); Fuzzy Sets as a Logic Canvas for Pattern Recognition (W Pedrycz & N Pizzi); Neural Network Based Pattern Recognition (V David Sanchez A); Networks of Spiking Neurons in Data Mining (K Cios & D M Sala); Genetic Algorithms, Pattern Classification and Neural Networks Design (S Bandyopadhyay et al.); Rough Sets in Pattern Recognition (A Skowron & R Swiniarski); Automated Generation of Qualitative Representations of Complex Objects by Hybrid Soft-Computing Methods (E H Ruspini & I S Zwir); Writing Speed and Writing Sequence Invariant On-line Handwriting Recognition (S-H Cha & S N Srihari); Tongue Diagnosis Based on Biometric Pattern Recognition Technology (K Wang et al.); and other papers. Readership: Graduate students, researchers and academics in pattern recognition.
| Author | : Hervé A. Bourlard |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 329 |
| Release | : 2012-12-06 |
| Genre | : Technology & Engineering |
| ISBN | : 1461532108 |
Download Connectionist Speech Recognition Book in PDF, ePub and Kindle
Connectionist Speech Recognition: A Hybrid Approach describes the theory and implementation of a method to incorporate neural network approaches into state of the art continuous speech recognition systems based on hidden Markov models (HMMs) to improve their performance. In this framework, neural networks (and in particular, multilayer perceptrons or MLPs) have been restricted to well-defined subtasks of the whole system, i.e. HMM emission probability estimation and feature extraction. The book describes a successful five-year international collaboration between the authors. The lessons learned form a case study that demonstrates how hybrid systems can be developed to combine neural networks with more traditional statistical approaches. The book illustrates both the advantages and limitations of neural networks in the framework of a statistical systems. Using standard databases and comparison with some conventional approaches, it is shown that MLP probability estimation can improve recognition performance. Other approaches are discussed, though there is no such unequivocal experimental result for these methods. Connectionist Speech Recognition is of use to anyone intending to use neural networks for speech recognition or within the framework provided by an existing successful statistical approach. This includes research and development groups working in the field of speech recognition, both with standard and neural network approaches, as well as other pattern recognition and/or neural network researchers. The book is also suitable as a text for advanced courses on neural networks or speech processing.
| Author | : Fabien Lauer |
| Publisher | : Springer |
| Total Pages | : 253 |
| Release | : 2018-10-04 |
| Genre | : Technology & Engineering |
| ISBN | : 3030001938 |
Download Hybrid System Identification Book in PDF, ePub and Kindle
Hybrid System Identification helps readers to build mathematical models of dynamical systems switching between different operating modes, from their experimental observations. It provides an overview of the interaction between system identification, machine learning and pattern recognition fields in explaining and analysing hybrid system identification. It emphasises the optimization and computational complexity issues that lie at the core of the problems considered and sets them aside from standard system identification problems. The book presents practical methods that leverage this complexity, as well as a broad view of state-of-the-art machine learning methods. The authors illustrate the key technical points using examples and figures to help the reader understand the material. The book includes an in-depth discussion and computational analysis of hybrid system identification problems, moving from the basic questions of the definition of hybrid systems and system identification to methods of hybrid system identification and the estimation of switched linear/affine and piecewise affine models. The authors also give an overview of the various applications of hybrid systems, discuss the connections to other fields, and describe more advanced material on recursive, state-space and nonlinear hybrid system identification. Hybrid System Identification includes a detailed exposition of major methods, which allows researchers and practitioners to acquaint themselves rapidly with state-of-the-art tools. The book is also a sound basis for graduate and undergraduate students studying this area of control, as the presentation and form of the book provides the background and coverage necessary for a full understanding of hybrid system identification, whether the reader is initially familiar with system identification related to hybrid systems or not.
| Author | : King Sun Fu |
| Publisher | : |
| Total Pages | : 58 |
| Release | : 1980 |
| Genre | : Pattern recognition systems |
| ISBN | : |
Download Hybrid Approaches and Industrial Applications of Pattern Recognition Book in PDF, ePub and Kindle
This report summarizes the major progress made during the support of NATO Research Grant 1639--On Hybrid Approaches to Pattern Recognition; Automatic Inspection by Lots in the Presence of Classification Errors; and Visual Screening of Integrated Circuits for Metallization Faults by Pattern Analysis Methods.
| Author | : Patricia Melin |
| Publisher | : Springer |
| Total Pages | : 272 |
| Release | : 2009-09-02 |
| Genre | : Computers |
| ISBN | : 9783540806158 |
Download Hybrid Intelligent Systems for Pattern Recognition Using Soft Computing Book in PDF, ePub and Kindle
This monograph describes new methods for intelligent pattern recognition using soft computing techniques including neural networks, fuzzy logic, and genetic algorithms. Hybrid intelligent systems that combine several soft computing techniques are needed due to the complexity of pattern recognition problems. Hybrid intelligent systems can have different architectures, which have an impact on the efficiency and accuracy of pattern recognition systems, to achieve the ultimate goal of pattern recognition. This book also shows results of the application of hybrid intelligent systems to real-world problems of face, fingerprint, and voice recognition. This monograph is intended to be a major reference for scientists and engineers applying new computational and mathematical tools to intelligent pattern recognition and can be also used as a textbook for graduate courses in soft computing, intelligent pattern recognition, computer vision, or applied artificial intelligence.
