Overview

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.

Full Product Details

Author:   Witold Pedrycz ,  Shyi-Ming Chen
Publisher:   Springer Nature Switzerland AG
Imprint:   Springer Nature Switzerland AG
Edition:   Softcover reprint of the original 1st ed. 2018
Volume:   777
Dimensions:   Width: 15.50cm , Height: 2.30cm , Length: 23.50cm
Weight:   0.664kg
ISBN:  

9783030078195

ISBN 10:   3030078191
Pages:   428
Publication Date:   30 January 2019
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Active
Availability:   Manufactured on demand  
We will order this item for you from a manufactured on demand supplier.

Table of Contents

Robust Constrained Concept Factorization.- An Automatic Cycling Performance Measurement System Based on ANFIS.- Fuzzy Classifiers Learned Through SVMs With Application to Specific Object Detection and Shape Extraction Using an RGB-D Camera.- Low Cost Parkinson’s Disease Early Detection and Classification Based on Voice and Electromyography Signal.- Particle Swarm Optimization Based HMM Parameter Estimation for Spectrum Sensing in Cognitive Radio System.- Improving Sparse Representation-Based Classification Using Local Principal Component Analysis.- Fuzzy Choquet Integration of Deep Convolutional Neural Networks for Remote Sensing.- Computational Intelligence for Pattern Recognition in EEG Signals.- Neural Network Based Physical Disorder Recognition for Elderly Health Care.- Deep Neural Networks for Structured Data.- Recognizing Subtle Micro-Facial Expressions Using Fuzzy Histogram of Optical Flow Orientations and Feature Selection Methods.- Granular Computing Techniques for Bioinformatics Pattern Recognition Problems in Non-Metric Spaces.- Multi-Classifier-Systems: Architectures, Algorithms and Applications.- Learning Label Dependency and Label Preference Relations in Graded Multi-Label Classification.- Improved Deep Neural Network Object Tracking System for Applications in Home Robotics.

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