Hybrid Intelligence for Image Analysis and Understanding
eBook - ePub

Hybrid Intelligence for Image Analysis and Understanding

  1. English
  2. ePUB (mobile friendly)
  3. Available on iOS & Android
eBook - ePub

Hybrid Intelligence for Image Analysis and Understanding

About this book

A synergy of techniques on hybrid intelligence for real-life image analysis

Hybrid Intelligence for Image Analysis and Understanding brings together research on the latest results and progress in the development of hybrid intelligent techniques for faithful image analysis and understanding. As such, the focus is on the methods of computational intelligence, with an emphasis on hybrid intelligent methods applied to image analysis and understanding.

The book offers a diverse range of hybrid intelligence techniques under the umbrellas of image thresholding, image segmentation, image analysis and video analysis.

Key features:

  • Provides in-depth analysis of hybrid intelligent paradigms.
  • Divided into self-contained chapters.
  • Provides ample case studies, illustrations and photographs of real-life examples to illustrate findings and applications of different hybrid intelligent paradigms.
  • Offers new solutions to recent problems in computer science, specifically in the application of hybrid intelligent techniques for image analysis and understanding, using well-known contemporary algorithms.

The book is essential reading for lecturers, researchers and graduate students in electrical engineering and computer science.

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Yes, you can access Hybrid Intelligence for Image Analysis and Understanding by Siddhartha Bhattacharyya, Indrajit Pan, Anirban Mukherjee, Paramartha Dutta, Siddhartha Bhattacharyya,Indrajit Pan,Anirban Mukherjee,Paramartha Dutta in PDF and/or ePUB format, as well as other popular books in Technology & Engineering & Electrical Engineering & Telecommunications. We have over one million books available in our catalogue for you to explore.

Table of contents

  1. Cover
  2. Title Page
  3. Copyright
  4. Dedication
  5. Table of Contents
  6. Editor Biographies
  7. List of Contributors
  8. Foreword
  9. Preface
  10. About the Companion website
  11. Chapter 1: Multilevel Image Segmentation Using Modified Genetic Algorithm (MfGA)-based Fuzzy C-Means
  12. Chapter 2: Character Recognition Using Entropy-Based Fuzzy C-Means Clustering
  13. Chapter 3: A Two-Stage Approach to Handwritten Indic Script Identification
  14. Chapter 4: Feature Extraction and Segmentation Techniques in a Static Hand Gesture Recognition System
  15. Chapter 5: SVM Combination for an Enhanced Prediction of Writers' Soft Biometrics
  16. Chapter 6: Brain-Inspired Machine Intelligence for Image Analysis: Convolutional Neural Networks
  17. Chapter 7: Human Behavioral Analysis Using Evolutionary Algorithms and Deep Learning
  18. Chapter 8: Feature-Based Robust Description and Monocular Detection: An Application to Vehicle tracking
  19. Chapter 9: A GIS Anchored Technique for Social Utility Hotspot Detection
  20. Chapter 10: Hyperspectral Data Processing: Spectral Unmixing, Classification, and Target Identification
  21. Chapter 11: A Hybrid Approach for Band Selection of Hyperspectral Images
  22. Chapter 12: Uncertainty-Based Clustering Algorithms for Medical Image Analysis
  23. Chapter 13: An Optimized Breast Cancer Diagnosis System Using a Cuckoo Search Algorithm and Support Vector Machine Classifier
  24. Chapter 14: Analysis of Hand Vein Images Using Hybrid Techniques
  25. Chapter 15: Identification of Abnormal Masses in Digital Mammogram Using Statistical Decision Making
  26. Chapter 16: Automatic Detection of Coronary Artery Stenosis Using Bayesian Classification and Gaussian Filters Based on Differential Evolution
  27. Chapter 17: Evaluating the Efficacy of Multi-resolution Texture Features for Prediction of Breast Density Using Mammographic Images
  28. Index
  29. End User License Agreement