Description
Fractals are infinite, complex patterns used in modeling physical and dynamic systems. Fractal theory research has increased across different fields of applications including engineering science, health science, and social science. Recent literature shows the vital role fractals play in digital image analysis, specifically in biomedical image processing. Fractal graphics is an interdisciplinary field that deals with how computers can be used to gain high-level understanding from digital images. Integrating artificial intelligence with fractal characteristics has resulted in new interdisciplinary research in the fields of pattern recognition and image processing analysis.Intelligent Fractal-Based Image Analysis: Application in Pattern Recognition and Machine Vision provides insights into the current strengths and weaknesses of different applications as well as research findings on fractal graphics in engineering and science applications. The book aims to improve the exchange of ideas and coherence between various core computing methods and highlight the relevance of related application areas for advanced as well as novice-user application. The book presents an in-depth look at core concepts, methodological aspects, and advanced feature opportunities, focusing on major real time applications in engineering science and health science. The book will appeal to researchers, data scientists, industry professionals, and graduate students in the fields of fractal graphics and its related applications.- Investigates advanced fractal theories spanning neural networks, fuzzy logic, machine learning, deep learning, and hybrid intelligent systems in solving pattern recognition problems- Explores the application of fractal theories to a wide range of medical image processing modalities- Presents case studies that illustrate the application and integration of fractal theories into intelligent computing in the resolution of important pattern recognition and machine vision problems
Table of Contents
Part 1: Intelligent Fractal-Based Image Analysis Introduction to Intelligent Fractal-Based Image Analysis – Editors 1.1 Insights into Intelligent Fractal-Based Image Analysis with Pattern Recognition 1.2 Analysis of Mandelbrot Set Fractal Images Using Machine Learning Based Approach 1.3 Chaos-based Image Encryption1.4 Fractal Feature-based Image Classification Part 2: Recognition Model Using Fractal Features 2.1 The study of Source Image and its Futuristic Quantum Applications: An insight from Fractal Analysis 2.2 Wavelet Multifractal Characterization of Anisotropic Oscillating Singularities and Application in Nanomaterials 2.3 GID-Net: Generic Image Denoising using Convolutional Auto-encoders 2.4 Geometrical Description of Image Analysis Using Fractal Theory Part 3: Fractals in Disease Identification and Control 3.1 Fractal Theory and the Explainable Artificial Intelligence of Cancer Medical Imaging 3.2 Computational Complexity of Multifractal Models-based MRI Image Processing for Subgroups of Multiple Sclerosis Patients' Diagnosis and Course in Precision Medicine 3.3 AI-Stochastic Fractal Analysis of the Alzheimer disease (AD) Medical Images 3.4 Preliminary Study of Retinal Lesions Classification on Rational Fundus Images for the Diagnosis of Retinal Diseases
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- 電子書籍
- 人件費適正化マニュアル
