| Description |
1 online resource (288 p.) |
| Series |
Studies in Computational Intelligence ; v.782 |
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Studies in computational intelligence ; v. 782
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| Contents |
Intro -- Preface -- Reference -- Contents -- Parallel 3-Parent Genetic Algorithm with Application to Routing in Wireless Mesh Networks -- 1 Introduction -- 2 P3PGA Algorithm -- 3 Simulated Performance, Results, and Discussion -- 4 P3PGA for Minimal Cost Route Evaluation -- 5 Implementation and Performance of the Proposed Approach -- 5.1 Comparative Performance of 100 Node Client WMNs -- 5.2 Comparative Performance of 500 Node Client WMNs -- 5.3 Comparative Performance of 1000 Node Client WMNs -- 5.4 Comparative Performance of 2000 Node Client WMNs |
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3.1 Approaches to Tracking a Single Hand -- 3.2 Approaches to Tracking Both Hands -- 4 Hand Shape and Finger-spelling Recognition -- 4.1 Rule-Based Approaches -- 4.2 Machine Learning Approaches -- 5 Hand Motion/Gesture Recognition -- 6 Summary and Conclusions -- References -- Automatic Sign Language Manual Parameter Recognition (II): Comprehensive System Design -- 1 Introduction -- 2 Hand Retrieval -- 2.1 Input Capture -- 2.2 Hand Detection -- 2.3 Skin Detection -- 2.4 Face Detection -- 2.5 Face Histogram Computation |
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3.2 Detailed DE Algorithm Description -- 3.2.1 Population Structure -- 3.2.2 Initialization -- 3.2.3 Mutation -- 3.2.4 Crossover -- 3.2.5 Selection -- 3.2.6 Termination -- 3.3 Self-Adaptive DE Algorithms -- 4 Population-Based Incremental Learning (PBIL) -- 4.1 Overview -- 4.2 Binary Encoding, Probability Vector, and Population -- 4.3 Mutation -- 4.4 Learning Process -- 4.5 Termination -- 5 Application of DE and PBIL to PSS Design -- 5.1 Overview -- 5.2 System Configurations -- 5.3 Single Machine Infinite Bus System: Results of Optimization |
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5.4 Two-Area Multimachine System: Results of Optimization -- 5.5 Sensitivity of Differential Evolution to Algorithm Control Parameters. -- 5.5.1 Effects of F and CR Parameters on DE Convergence -- 5.5.2 Effect of Population Size -- 5.6 Application of Adaptive DE to PSS Design -- 5.7 Performance Summary -- 6 Chapter Summary -- References -- Automatic Sign Language Manual Parameter Recognition (I): Survey -- 1 Background and Motivation -- 2 Skin Detection -- 2.1 Static Skin Detection -- 2.2 Parametric Skin Detection -- 2.3 Non-parametric Skin Detection -- 3 Hand Tracking |
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5.5 Comparative Performance of 2500 Node Client WMNs -- 5.6 Overall Performance Considering all Networks -- 6 Conclusions -- References -- Application of Evolutionary Algorithms to Power System Stabilizer Design -- 1 Introduction -- 1.1 Oscillations in Electrical Power Systems and Power Systems Stabilizers -- 1.2 Algorithms for Parameter Optimization: Differential Evolution and Population-Based Incremental Learning -- 2 Problem Statement -- 2.1 Overview -- 2.2 State-Space Representation -- 2.3 Linearization -- 2.4 Modal Analysis -- 3 The Differential Evolution Algorithm -- 3.1 Overview |
| Summary |
This book provides step-by-step explanations of successful implementations and practical applications of machine learning. The books GitHub page contains software codes to assist readers in adapting materials and methods for their own use. A wide variety of applications are discussed, including wireless mesh network and power systems optimization; computer vision; image and facial recognition; protein prediction; data mining; and data discovery. Numerous state-of-the-art machine learning techniques are employed (with detailed explanations), including biologically-inspired optimization (genetic and other evolutionary algorithms, swarm intelligence); Viola Jones face detection; Gaussian mixture modeling; support vector machines; deep convolutional neural networks with performance enhancement techniques (including network design, learning rate optimization, data augmentation, transfer learning); spiking neural networks and timing dependent plasticity; frequent itemset mining; binary classification; and dynamic programming. This book provides valuable information on effective, cutting-edge techniques, and approaches for students, researchers, practitioners, and teachers in the field of machine learning. Presents practical, useful applications of machine learning for practitioners, students, and researchers Provides hands-on tools for a variety of machine learning techniques Covers evolutionary and swarm intelligence, facial and image recognition, deep learning, data mining and discovery, and statistical techniques |
| Notes |
2.6 Enhanced Skin Highlighting Principle and Its Application to the Left and Right Hands |
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Description based upon print version of record |
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Includes index |
| Subject |
Machine learning.
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Artificial intelligence.
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Communications engineering / telecommunications.
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Computers -- Database Management -- Data Mining.
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Cybernetics & systems theory.
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Data mining.
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Machine learning.
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Medical equipment & techniques.
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Medical -- General.
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Molecular biology.
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Science -- Life Sciences -- Anatomy & Physiology.
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Technology & Engineering -- Engineering (General).
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Technology & Engineering -- Telecommunications.
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| Genre/Form |
Electronic books.
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| Form |
Electronic book
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| Author |
Subair, Saad
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|
Thron, Christopher
|
| ISBN |
3030378306 |
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9783030378301 |
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