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Intelligent Fractal-Based Image Analysis

Intelligent Fractal-Based Image Analysis
Author: Soumya Ranjan Nayak
Publisher: Elsevier
Total Pages: 320
Release: 2024-06-14
Genre: Computers
ISBN: 0443184690
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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

Examining Fractal Image Processing and Analysis

Examining Fractal Image Processing and Analysis
Author: Nayak, Soumya Ranjan
Publisher: IGI Global
Total Pages: 305
Release: 2019-10-18
Genre: Computers
ISBN: 1799800687
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Digital image processing is a field that is constantly improving. Gaining high-level understanding from digital images is a key requirement for computing. One aspect of study that is assisting with this advancement is fractal theory. This new science has gained momentum and popularity as it has become a key topic of research in the area of image analysis. Examining Fractal Image Processing and Analysis is an essential reference source that discusses fractal theory applications and analysis, including box-counting analysis, multi-fractal analysis, 3D fractal analysis, and chaos theory, as well as recent trends in other soft computing techniques. Featuring research on topics such as image compression, pattern matching, and artificial neural networks, this book is ideally designed for system engineers, computer engineers, professionals, academicians, researchers, and students seeking coverage on problem-oriented processing techniques and imaging technologies.

Computational Intelligence in Image Processing

Computational Intelligence in Image Processing
Author: Amitava Chatterjee
Publisher: Springer Science & Business Media
Total Pages: 303
Release: 2012-08-10
Genre: Technology & Engineering
ISBN: 3642306217
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Computational intelligence based techniques have firmly established themselves as viable, alternate, mathematical tools for more than a decade. They have been extensively employed in many systems and application domains, among these signal processing, automatic control, industrial and consumer electronics, robotics, finance, manufacturing systems, electric power systems, and power electronics. Image processing is also an extremely potent area which has attracted the attention of many researchers who are interested in the development of new computational intelligence-based techniques and their suitable applications, in both research problems and in real-world problems. Part I of the book discusses several image preprocessing algorithms; Part II broadly covers image compression algorithms; Part III demonstrates how computational intelligence-based techniques can be effectively utilized for image analysis purposes; and Part IV shows how pattern recognition, classification and clustering-based techniques can be developed for the purpose of image inferencing. The book offers a unified view of the modern computational intelligence techniques required to solve real-world problems and it is suitable as a reference for engineers, researchers and graduate students.

Examining Fractal Image Processing and Analysis

Examining Fractal Image Processing and Analysis
Author:
Publisher:
Total Pages:
Release: 2020
Genre:
ISBN: 9781799810698
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Digital image processing is a field that is constantly improving. Gaining high-level understanding from digital images is a key requirement for computing. One aspect of study that is assisting with this advancement is fractal theory. This new science has gained momentum and popularity as it has become a key topic of research in the area of image analysis. Examining Fractal Image Processing and Analysis is an essential reference source that discusses fractal theory applications and analysis, including box-counting analysis, multi-fractal analysis, 3D fractal analysis, and chaos theory, as well as recent trends in other soft computing techniques. Featuring research on topics such as image compression, pattern matching, and artificial neural networks, this book is ideally designed for system engineers, computer engineers, professionals, academicians, researchers, and students seeking coverage on problem-oriented processing techniques and imaging technologies.

Modern Advances in Applied Intelligence

Modern Advances in Applied Intelligence
Author: Moonis Ali
Publisher: Springer
Total Pages: 543
Release: 2014-05-20
Genre: Computers
ISBN: 3319074679
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The two volume set LNAI 8481 and 8482 constitutes the refereed conference proceedings of the 27th International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2014, held in Kaohsiung, Taiwan, in June 2014. The total of 106 papers selected for the proceedings were carefully reviewed and selected from various submissions. The papers deal with a wide range of topics from applications of applied intelligent systems to solve real-life problems in all areas including engineering, science, industry, automation and robotics, business and finance, medicine and biomedicine, bioinformatics, cyberspace and human-machine interaction.

Computational Intelligence in Data Mining

Computational Intelligence in Data Mining
Author: Himansu Sekhar Behera
Publisher: Springer
Total Pages: 847
Release: 2017-05-19
Genre: Technology & Engineering
ISBN: 9811038740
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The book presents high quality papers presented at the International Conference on Computational Intelligence in Data Mining (ICCIDM 2016) organized by School of Computer Engineering, Kalinga Institute of Industrial Technology (KIIT), Bhubaneswar, Odisha, India during December 10 – 11, 2016. The book disseminates the knowledge about innovative, active research directions in the field of data mining, machine and computational intelligence, along with current issues and applications of related topics. The volume aims to explicate and address the difficulties and challenges that of seamless integration of the two core disciplines of computer science.

Artificial Intelligence-based Infrared Thermal Image Processing and its Applications

Artificial Intelligence-based Infrared Thermal Image Processing and its Applications
Author: U. Snekhalatha
Publisher: CRC Press
Total Pages: 247
Release: 2022-09-28
Genre: Medical
ISBN: 1000688402
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Infrared thermography is a fast and non-invasive technology that provides a map of the temperature distribution on the body’s surface. This book provides a description of designing and developing a computer-assisted diagnosis (CAD) system based on thermography for diagnosing such common ailments as rheumatoid arthritis (RA), diabetes complications, and fever. It also introduces applications of machine-learning and deep-learning methods in the development of CAD systems. Key Features: Covers applications of various image processing techniques in thermal imaging applications for the diagnosis of different medical conditions Describes the development of a computer diagnostics system (CAD) based on thermographic data Discusses deep-learning models for accurate diagnosis of various diseases Includes new aspects in rheumatoid arthritis and diabetes research using advanced analytical tools Reviews application of feature fusion algorithms and feature reduction algorithms for accurate classification of images This book is aimed at researchers and graduate students in biomedical engineering, medicine, image processing, and CAD.

Computational Intelligence in Pattern Recognition

Computational Intelligence in Pattern Recognition
Author: Asit Kumar Das
Publisher: Springer Nature
Total Pages: 692
Release: 2022-06-20
Genre: Technology & Engineering
ISBN: 9811930899
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This book features high-quality research papers presented at the 4th International Conference on Computational Intelligence in Pattern Recognition (CIPR 2022), held at Indian Institute of Engineering Science and Technology, Shibpur, Howrah, West Bengal, India, during 23 – 24 April 2022. It includes practical development experiences in various areas of data analysis and pattern recognition, focusing on soft computing technologies, clustering and classification algorithms, rough set and fuzzy set theory, evolutionary computations, neural science and neural network systems, image processing, combinatorial pattern matching, social network analysis, audio and video data analysis, data mining in dynamic environments, bioinformatics, hybrid computing, big data analytics and deep learning. It also provides innovative solutions to the challenges in these areas and discusses recent developments.

Artificial Intelligence in Recognition and Classification of Astrophysical and Medical Images

Artificial Intelligence in Recognition and Classification of Astrophysical and Medical Images
Author: Valentina Zharkova
Publisher: Springer Science & Business Media
Total Pages: 388
Release: 2007-03-07
Genre: Computers
ISBN: 3540475117
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This book presents innovative techniques in recognition and classification of astrophysical and medical images. Coverage includes: image standardization and enhancement; region-based methods for pattern recognition in medical and astrophysical images; advanced information processing using statistical methods; and feature recognition and classification using spectral method.

Multi-Chaos, Fractal and Multi-Fractional Artificial Intelligence of Different Complex Systems

Multi-Chaos, Fractal and Multi-Fractional Artificial Intelligence of Different Complex Systems
Author: Yeliz Karaca
Publisher: Academic Press
Total Pages: 352
Release: 2022-06-22
Genre: Science
ISBN: 0323886167
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Multi-Chaos, Fractal and Multi-Fractional Artificial Intelligence of Different Complex Systems addresses different uncertain processes inherent in the complex systems, attempting to provide global and robust optimized solutions distinctively through multifarious methods, technical analyses, modeling, optimization processes, numerical simulations, case studies as well as applications including theoretical aspects of complexity. Foregrounding Multi-chaos, Fractal and Multi-fractional in the era of Artificial Intelligence (AI), the edited book deals with multi- chaos, fractal, multifractional, fractional calculus, fractional operators, quantum, wavelet, entropy-based applications, artificial intelligence, mathematics-informed and data driven processes aside from the means of modelling, and simulations for the solution of multifaceted problems characterized by nonlinearity, non-regularity and self-similarity, frequently encountered in different complex systems. The fundamental interacting components underlying complexity, complexity thinking, processes and theory along with computational processes and technologies, with machine learning as the core component of AI demonstrate the enabling of complex data to augment some critical human skills. Appealing to an interdisciplinary network of scientists and researchers to disseminate the theory and application in medicine, neurology, mathematics, physics, biology, chemistry, information theory, engineering, computer science, social sciences and other far-reaching domains, the overarching aim is to empower out-of-the-box thinking through multifarious methods, directed towards paradoxical situations, uncertain processes, chaotic, transient and nonlinear dynamics of complex systems. Constructs and presents a multifarious approach for critical decision-making processes embodying paradoxes and uncertainty. Includes a combination of theory and applications with regard to multi-chaos, fractal and multi-fractional as well as AI of different complex systems and many-body systems. Provides readers with a bridge between application of advanced computational mathematical methods and AI based on comprehensive analyses and broad theories.