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Hybrid Soft Computing for Image Segmentation

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Cover of 'Hybrid Soft Computing for Image Segmentation'

Table of Contents

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    Book Overview
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    Chapter 1 Hybrid Swarms Optimization Based Image Segmentation
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    Chapter 2 Grayscale Image Segmentation Using Multilevel Thresholding and Nature-Inspired Algorithms
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    Chapter 3 A Novel Hybrid CS-BFO Algorithm for Optimal Multilevel Image Thresholding Using Edge Magnitude Information
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    Chapter 4 REFII Model and Fuzzy Logic as a Tool for Image Classification Based on Image Example
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    Chapter 5 Microscopic Image Segmentation Using Hybrid Technique for Dengue Prediction
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    Chapter 6 Extraction of Knowledge Rules for the Retrieval of Mesoscale Oceanic Structures in Ocean Satellite Images
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    Chapter 7 Hybrid Uncertainty-Based Techniques for Segmentation of Satellite Imagery and Applications
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    Chapter 8 Improved Human Skin Segmentation Using Fuzzy Fusion Based on Optimized Thresholds by Genetic Algorithms
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    Chapter 9 Uncertainty-Based Spatial Data Clustering Algorithms for Image Segmentation
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    Chapter 10 Coronary Artery Segmentation and Width Estimation Using Gabor Filters and Evolutionary Computation Techniques
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    Chapter 11 Hybrid Intelligent Techniques for Segmentation of Breast Thermograms
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    Chapter 12 Modeling of High-Dimensional Data for Applications of Image Segmentation in Image Retrieval and Recognition Tasks
Attention for Chapter 12: Modeling of High-Dimensional Data for Applications of Image Segmentation in Image Retrieval and Recognition Tasks
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Citations

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Chapter title
Modeling of High-Dimensional Data for Applications of Image Segmentation in Image Retrieval and Recognition Tasks
Chapter number 12
Book title
Hybrid Soft Computing for Image Segmentation
Published by
Springer International Publishing, November 2016
DOI 10.1007/978-3-319-47223-2_12
Book ISBNs
978-3-31-947222-5, 978-3-31-947223-2
Authors

Dariusz Jakóbczak

Editors

Siddhartha Bhattacharyya, Paramartha Dutta, Sourav De, Goran Klepac

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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 > Master 2 100%
Readers by discipline Count As %
Computer Science 1 50%
Earth and Planetary Sciences 1 50%

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