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Hybrid Soft Computing for Image Segmentation

Overview of attention for book
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 9: Uncertainty-Based Spatial Data Clustering Algorithms for Image Segmentation
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Citations

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Chapter title
Uncertainty-Based Spatial Data Clustering Algorithms for Image Segmentation
Chapter number 9
Book title
Hybrid Soft Computing for Image Segmentation
Published by
Springer International Publishing, November 2016
DOI 10.1007/978-3-319-47223-2_9
Book ISBNs
978-3-31-947222-5, 978-3-31-947223-2
Authors

Deepthi P. Hudedagaddi, B. K. Tripathy

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 3 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 3 100%

Demographic breakdown

Readers by professional status Count As %
Professor 1 33%
Student > Master 1 33%
Unknown 1 33%
Readers by discipline Count As %
Computer Science 1 33%
Earth and Planetary Sciences 1 33%
Unknown 1 33%

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