Hybrid Metaheuristics for Image Analysis
Editors: Bhattacharyya, Siddhartha (Ed.)
- Contributions provide a multidimensional approach
- Useful for researchers in computer science, electrical engineering, and information technology
- Explains various soft computing techniques
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- About this book
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This book presents contributions in the field of computational intelligence for the purpose of image analysis. The chapters discuss how problems such as image segmentation, edge detection, face recognition, feature extraction, and image contrast enhancement can be solved using techniques such as genetic algorithms and particle swarm optimization.
The contributions provide a multidimensional approach, and the book will be useful for researchers in computer science, electrical engineering, and information technology.
- Table of contents (9 chapters)
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Current and Future Trends in Segmenting Satellite Images Using Hybrid and Dynamic Genetic Algorithms
Pages 1-31
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A Hybrid Metaheuristic Algorithm Based on Quantum Genetic Computing for Image Segmentation
Pages 33-48
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Genetic Algorithm Implementation to Optimize the Hybridization of Feature Extraction and Metaheuristic Classifiers
Pages 49-86
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Optimization of a HMM-Based Hand Gesture Recognition System Using a Hybrid Cuckoo Search Algorithm
Pages 87-114
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Satellite Image Contrast Enhancement Using Fuzzy Termite Colony Optimization
Pages 115-144
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Table of contents (9 chapters)
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Bibliographic Information
- Bibliographic Information
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- Book Title
- Hybrid Metaheuristics for Image Analysis
- Editors
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- Siddhartha Bhattacharyya
- Copyright
- 2018
- Publisher
- Springer International Publishing
- Copyright Holder
- Springer International Publishing AG, part of Springer Nature
- eBook ISBN
- 978-3-319-77625-5
- DOI
- 10.1007/978-3-319-77625-5
- Hardcover ISBN
- 978-3-319-77624-8
- Softcover ISBN
- 978-3-030-08497-4
- Edition Number
- 1
- Number of Pages
- XII, 256
- Number of Illustrations
- 50 b/w illustrations, 50 illustrations in colour
- Topics
