Bio-inspired Hybrid Intelligent Systems for Image Analysis and Pattern Recognition [electronic resource] / edited by Patricia Melin, Janusz Kacprzyk, Witold Pedrycz.

By: Melin, Patricia [editor.]Contributor(s): Kacprzyk, Janusz [editor.] | Pedrycz, Witold [editor.] | SpringerLink (Online service)Material type: TextTextLanguage: English Series: Studies in Computational Intelligence: 256Publisher: Berlin, Heidelberg : Springer Berlin Heidelberg, 2009Description: VIII, 263 p. online resourceContent type: text Media type: computer Carrier type: online resourceISBN: 9783642045165Subject(s): Engineering | Artificial intelligence | Computer vision | Engineering mathematics | Engineering | Appl.Mathematics/Computational Methods of Engineering | Artificial Intelligence (incl. Robotics) | Signal, Image and Speech Processing | Computer Imaging, Vision, Pattern Recognition and GraphicsAdditional physical formats: Printed edition:: No titleDDC classification: 519 LOC classification: TA329-348TA640-643Online resources: Click here to access online
Contents:
Introductory Concepts and Models -- A Survey of Applications of the Extensions of Fuzzy Sets to Image Processing -- Interval Type-2 Fuzzy Cellular Model Applied to the Dynamics of a Uni-specific Population Induced by Environment Variations -- A Genetic Programming Approach to the Design of Interest Point Operators -- Modular Neural Networks in Pattern Recognition -- Face, Fingerprint and Voice Recognition with Modular Neural Networks and Fuzzy Integration -- Modular Neural Networks with Fuzzy Response Integration for Signature Recognition -- Intelligent Hybrid System for Person Identification Using Biometric Measures and Modular Neural Networks with Fuzzy Integration of Responses -- Optimization of Modular Neural Networks with Interval Type-2 Fuzzy Logic Integration Using an Evolutionary Method with Application to Multimodal Biometry -- Comparative Study of Fuzzy Methods for Response Integration in Ensemble Neural Networks for Pattern Recognition -- Neural Network Models and Time Series Prediction -- Ensemble Neural Networks with Fuzzy Integration for Complex Time Series Prediction -- Prediction of the MXNUSD Exchange Rate Using Hybrid IT2 FLS Forecaster -- Discovering Universal Polynomial Cellular Neural Networks through Genetic Algorithms -- EMG Hand Burst Activity Detection Study Based on Hard and Soft Thresholding -- Optimization and Robotics -- Modular Neural Networks Architecture Optimization with a New Evolutionary Method Using a Fuzzy Combination Particle Swarm Optimization and Genetic Algorithms -- A Multi-agent Architecture for Controlling Autonomous Mobile Robots Using Fuzzy Logic and Obstacle Avoidance with Computer Vision -- Particle Swarm Optimization Applied to the Design of Type-1 and Type-2 Fuzzy Controllers for an Autonomous Mobile Robot.
In: Springer eBooksSummary: "Bio-Inspired Hybrid Intelligent Systems for Image Analysis and Pattern Recognition" comprises papers on diverse aspects of bio-inspired models, soft computing and hybrid intelligent systems. The articles are divided in four main parts. The first one consists of papers that propose new fuzzy and bio-inspired models to solve general problems. The second part deals with the main theme of modular neural networks in pattern recognition, which are basically papers using bio-inspired techniques. The third part contains papers that apply hybrid intelligent systems to the problem of time series analysis and prediction, while the fourth one shows papers dealing with bio-inspired models in optimization and robotics applications. An edited book where both theoretical and application aspects are covered.
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Introductory Concepts and Models -- A Survey of Applications of the Extensions of Fuzzy Sets to Image Processing -- Interval Type-2 Fuzzy Cellular Model Applied to the Dynamics of a Uni-specific Population Induced by Environment Variations -- A Genetic Programming Approach to the Design of Interest Point Operators -- Modular Neural Networks in Pattern Recognition -- Face, Fingerprint and Voice Recognition with Modular Neural Networks and Fuzzy Integration -- Modular Neural Networks with Fuzzy Response Integration for Signature Recognition -- Intelligent Hybrid System for Person Identification Using Biometric Measures and Modular Neural Networks with Fuzzy Integration of Responses -- Optimization of Modular Neural Networks with Interval Type-2 Fuzzy Logic Integration Using an Evolutionary Method with Application to Multimodal Biometry -- Comparative Study of Fuzzy Methods for Response Integration in Ensemble Neural Networks for Pattern Recognition -- Neural Network Models and Time Series Prediction -- Ensemble Neural Networks with Fuzzy Integration for Complex Time Series Prediction -- Prediction of the MXNUSD Exchange Rate Using Hybrid IT2 FLS Forecaster -- Discovering Universal Polynomial Cellular Neural Networks through Genetic Algorithms -- EMG Hand Burst Activity Detection Study Based on Hard and Soft Thresholding -- Optimization and Robotics -- Modular Neural Networks Architecture Optimization with a New Evolutionary Method Using a Fuzzy Combination Particle Swarm Optimization and Genetic Algorithms -- A Multi-agent Architecture for Controlling Autonomous Mobile Robots Using Fuzzy Logic and Obstacle Avoidance with Computer Vision -- Particle Swarm Optimization Applied to the Design of Type-1 and Type-2 Fuzzy Controllers for an Autonomous Mobile Robot.

"Bio-Inspired Hybrid Intelligent Systems for Image Analysis and Pattern Recognition" comprises papers on diverse aspects of bio-inspired models, soft computing and hybrid intelligent systems. The articles are divided in four main parts. The first one consists of papers that propose new fuzzy and bio-inspired models to solve general problems. The second part deals with the main theme of modular neural networks in pattern recognition, which are basically papers using bio-inspired techniques. The third part contains papers that apply hybrid intelligent systems to the problem of time series analysis and prediction, while the fourth one shows papers dealing with bio-inspired models in optimization and robotics applications. An edited book where both theoretical and application aspects are covered.

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