Hybrid Methods in Pattern Recognition PDF Download
Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download Hybrid Methods in Pattern Recognition PDF full book. Access full book title Hybrid Methods in Pattern Recognition by Horst Bunke. Download full books in PDF and EPUB format.
Author: Horst Bunke
Publisher: World Scientific
ISBN: 9810248326
Category : Technology & Engineering
Languages : en
Pages : 338
Get Book
Book Description
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: Horst Bunke
Publisher: World Scientific
ISBN: 9810248326
Category : Technology & Engineering
Languages : en
Pages : 338
Get Book
Book Description
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: Patricia Melin
Publisher: Springer
ISBN: 9783642063251
Category : Computers
Languages : en
Pages : 0
Get Book
Book Description
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.
Author: Siddhartha Bhattacharyya
Publisher: CRC Press
ISBN: 1351650203
Category : Computers
Languages : en
Pages : 552
Get Book
Book Description
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
ISBN: 012818700X
Category : Computers
Languages : en
Pages : 250
Get Book
Book Description
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: Horst Bunke
Publisher: World Scientific
ISBN: 9789971505660
Category : Computers
Languages : en
Pages : 568
Get Book
Book Description
This book is currently the only one on this subject containing both introductory material and advanced recent research results. It presents, at one end, fundamental concepts and notations developed in syntactic and structural pattern recognition and at the other, reports on the current state of the art with respect to both methodology and applications. In particular, it includes artificial intelligence related techniques, which are likely to become very important in future pattern recognition.The book consists of individual chapters written by different authors. The chapters are grouped into broader subject areas like “Syntactic Representation and Parsing”, “Structural Representation and Matching”, “Learning”, etc. Each chapter is a self-contained presentation of one particular topic. In order to keep the original flavor of each contribution, no efforts were undertaken to unify the different chapters with respect to notation. Naturally, the self-containedness of the individual chapters results in some redundancy. However, we believe that this handicap is compensated by the fact that each contribution can be read individually without prior study of the preceding chapters. A unification of the spectrum of material covered by the individual chapters is provided by the subject and author index included at the end of the book.
Author: E.S. Gelsema
Publisher: North Holland
ISBN:
Category : Computers
Languages : en
Pages : 600
Get Book
Book Description
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: Patricia Melin
Publisher: Springer
ISBN: 9783540806158
Category : Computers
Languages : en
Pages : 272
Get Book
Book Description
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.
Author: Sankar K. Pal
Publisher: World Scientific
ISBN: 9789812386533
Category : Computers
Languages : en
Pages : 644
Get Book
Book Description
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: Jeng-Shyang Pan
Publisher: Springer
ISBN: 364240846X
Category : Computers
Languages : en
Pages : 691
Get Book
Book Description
This volume constitutes the proceedings of the 8th International Conference on Hybrid Artificial Intelligent Systems, HAIS 2013, held in Salamanca, Spain, in September 2013. The 68 papers published in this volume were carefully reviewed and selected from 218 submissions. They are organized in topical sessions on Agents and Multi Agents Systems; HAIS Applications; Classification and Cluster Analysis; Data Mining and Knowledge Discovery; Video and Image Analysis; Bio-inspired Models and Evolutionary Computation; Learning Algorithms; Systems, MAN, and Cybernetics; Hybrid Intelligent Systems for Data Mining and Applications; Metaheuristics for Combinatorial Optimization and Modelling Complex Systems.
Author: Hervé A. Bourlard
Publisher: Springer Science & Business Media
ISBN: 1461532108
Category : Technology & Engineering
Languages : en
Pages : 329
Get Book
Book Description
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.
