Computational Intelligence for Pattern Recognition (eBook, PDF)

Redaktion: Pedrycz, Witold; Chen, Shyi-Ming

• Format: PDF

Produktbeschreibung

Provides a comprehensive and up-to-date treatise, covering a spectrum of methodological and algorithmic issues, and discussing implementations and case studies

Identifies best design practices, assessing business models and practices of pattern recognition in industry, health care, administration, and business

Systematic exposure of the concepts, design methodology, and detailed algorithms

Individual chapters with clearly delineated agenda and well-defined focus and additional reading material available via carefully selected references

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Produktdetails

• Verlag: Springer International Publishing
• Seitenzahl: 428
• Erscheinungstermin: 30. April 2018
• Englisch
• ISBN-13: 9783319896298
• Artikelnr.: 52499050

Inhaltsangabe

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.