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Practical Applications of Computational Intelligence Techniques

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Cover of 'Practical Applications of Computational Intelligence Techniques'

Table of Contents

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    Book Overview
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    Chapter 1 An Introduction to Computational Intelligence Paradigms
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    Chapter 2 Networked Virtual Park
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    Chapter 3 Commercial Coin Recognisers Using Neural and Fuzzy Techniques
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    Chapter 4 Fuzzy Techniques in Intelligent Household Appliances
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    Chapter 5 Neural Prediction in Industry: Increasing Reliability through Use of Confidence Measures and Model Combination
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    Chapter 6 Handling the Back Calculation Problem in Aerial Spray Models Using a Genetic Algorithm
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    Chapter 7 Genetic Algorithm Optimization of a Filament Winding Process Modeled in WITNESS
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    Chapter 8 Genetic Algorithm for Optimizing the Gust Loads for Predicting Aircraft Loads and Dynamic Response
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    Chapter 9 A Stochastic Dynamic Programming Technique for Property Market Timing
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    Chapter 10 A Hybrid Approach to Breast Cancer Diagnosis
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    Chapter 11 Artificial Neural Networks as a Computer Aid for Lung Disease Detection and Classification in Ventilation-Perfusion Lung Scans
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    Chapter 12 Neural Network for Classification of Focal Liver Lesions in Ultrasound Images
Attention for Chapter 11: Artificial Neural Networks as a Computer Aid for Lung Disease Detection and Classification in Ventilation-Perfusion Lung Scans
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Citations

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Chapter title
Artificial Neural Networks as a Computer Aid for Lung Disease Detection and Classification in Ventilation-Perfusion Lung Scans
Chapter number 11
Book title
Practical Applications of Computational Intelligence Techniques
Published by
Springer, Dordrecht, January 2001
DOI 10.1007/978-94-010-0678-1_11
Book ISBNs
978-9-40-103868-3, 978-9-40-100678-1
Authors

G. D. Tourassi, E. D. Frederick, R. E. Coleman

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 2 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 2 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 1 50%
Professor 1 50%
Readers by discipline Count As %
Computer Science 2 100%

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