Artificial Intelligence and Machine Learning Techniques in Image Processing and Computer Vision

Cover....1

Half Title....2

Title Page....4

Copyright Page....5

Series Page....6

About the Editors....10

Table of Contents....12

Contributors....14

Abbreviations....18

Preface....22

Part I: Health Care Systems....26

1. Machine Learning Model-Based Detection of Sperm Head Abnormalities from Stained Microscopic Images....28

2. Smart Healthcare System for Reliable Diagnosis of Polycystic Ovary Syndrome....44

3. Classification of Breast Histopathological Images using Semi-Supervised Generative Adversarial Networks....62

4. A Systematic Review for the Classification and Segmentation of Diabetic Retinopathy Lesion from Fundus....80

5. Critical Analysis of Various Supervised Machine Learning Algorithms for Detecting Diabetic Retinopathy in Images....100

Part II: Image and Video Processing....120

6. Artificial Bee Colony Optimization Technique-Based Video Copyright Protection in DWT-PCA Domain....122

7. Gray Tone Spatial Dependence Matrix: Texture Feature for Image Classification....136

8. Image Colorization and Restoration Using Deep Learning....156

9. Determining Image Scale in Real-World Units Using Natural Objects Present in Image....170

10. Image Segmentation Using Metaheuristic....194

Part III: Advanced Machine Learning....216

11. A Computer Vision Use Case: Detecting the Changes in Amazon Rainforest Over Time....218

12. Using CNN and Image Processing Approaches in the Preservation of Sea Turtles....232

13. Deep Learning-Based Semantic Segmentation Techniques and Their Applications in Remote Sensing....254

14. Deep Convolutional Neural Network-Based Single Image Superresolution....284

15 A Review of Machine Learning Techniques for Vision-Established Human Action Recognition....310

Index....334

This new volume provides in-depth and detailed knowledge about the latest research in image processing and computer vision techniques. Explaining the machine learning algorithms and models involved, the authors differentiate between the various algorithms available and how to choose which to use for the most precise results for a specific task involving certain constraints. The volume provides real-world examples to illustrate the concepts and methods.

The authors discuss machine learning in healthcare systems for detection, diagnosis, classification, and segmentation. They also explore the diverse applications of image and video processing, including image colorization and restoration using deep learning, using machine learning to record the climate changes in over time with remote sensing, and more.