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Pattern recognition in soft computing paradigm /
Pattern recognition (PR) consists of three important tasks: feature analysis, clustering and classification. Image analysis can also be viewed as a PR task. Feature analysis is a very important step in designing any useful PR system because its effectiveness depends heavily on the set of features us...
| Clasificación: | Libro Electrónico |
|---|---|
| Otros Autores: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Singapore ; New Jersey :
World Scientific,
©2001.
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| Colección: | FLSI soft computing series ;
v. 2. |
| Temas: | |
| Acceso en línea: | Texto completo |
Tabla de Contenidos:
- Series Editor's Preface ; Volume Editor's Preface ; Chapter 1 Dimensionality Reduction Techniques for Interactive Visualization, Exploratory Data Analysis and Classification; 1.1 Introduction ; 1.2 Feature Extraction and Multivariate Data Projection ; 1.3 Interactive Data Visualisation and Explorative Analysis
- 1.4 Advanced Projection Methods 1.5 Conclusions and Future Work ; References ; Chapter 2 The Self-Organizing Map as a Tool in Knowledge Engineering ; 2.1 Introduction ; 2.2 Data analysis using the Self-Organizing Map ; 2.3 Visualization ; 2.4 Software ; 2.5 Case studies
- 2.6 Conclusions 2.7 Acknowledgments ; References ; Chapter 3 Classification of Oceanic Water Types Using Self-organizing Feature Maps ; 3.1 Introduction ; 3.2 Unsupervised neural networks for ocean colour data processing
- 3.3 Hierarchy of neural networks for the water type classification 3.4 Accomplishments of the hierarchical image processing ; 3.5 Conclusions ; References ; Chapter 4 Feature Selection by Artificial Neural Network for Pattern Classification ; 4.1 Introduction
- 4.2 Fractal Neural Network Model 4.3 Feature Selection Algorithm ; 4.4 Simulation and Results ; 4.5 Discussion and Conclusion ; References ; Chapter 5 MLP Based Character Recognition using Fuzzy Features and a Genetic Algorithm for Feature Selection ; 5.1 Introduction