Computational Intelligence for Pattern Recognition

Computational Intelligence for Pattern Recognition edited by Witold Pedrycz, Shyi-Ming Chen.

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 reco...

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Bibliographic Details
Corporate Author: SpringerLink (Online service)
Other Authors: Pedrycz, Witold (Editor), Chen, Shyi-Ming (Editor)
Format: eBook
Language:English
Published: Cham : Springer International Publishing : Imprint: Springer, 2018.
Edition:1st ed. 2018.
Series:Studies in Computational Intelligence, 777
Springer eBook Collection.
Subjects:
Computational intelligence.
Artificial intelligence.
Pattern recognition.
Electronic resources (E-books)
Online Access:Click to view e-book
Holy Cross Note:Loaded electronically.
Electronic access restricted to members of the Holy Cross Community.
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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