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Author: Soumya Ranjan Nayak
Publisher: Elsevier
ISBN: 0443184690
Category : Computers
Languages : en
Pages : 320
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Book 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
Author: Soumya Ranjan Nayak
Publisher: Elsevier
ISBN: 0443184690
Category : Computers
Languages : en
Pages : 320
Get Book Here
Book 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
Author: Amitava Chatterjee
Publisher: Springer Science & Business Media
ISBN: 3642306217
Category : Technology & Engineering
Languages : en
Pages : 303
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Book Description
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.
Author: Yeliz Karaca
Publisher: Academic Press
ISBN: 0323886167
Category : Science
Languages : en
Pages : 352
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Book Description
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.
Author: Roumen Kountchev
Publisher: Springer
ISBN: 3319321927
Category : Technology & Engineering
Languages : en
Pages : 389
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Book Description
This book presents an Introduction and 11 independent chapters, which are devoted to various new approaches of intelligent image processing and analysis. The book also presents new methods, algorithms and applied systems for intelligent image processing, on the following basic topics: Methods for Hierarchical Image Decomposition; Intelligent Digital Signal Processing and Feature Extraction; Data Clustering and Visualization via Echo State Networks; Clustering of Natural Images in Automatic Image Annotation Systems; Control System for Remote Sensing Image Processing; Tissue Segmentation of MR Brain Images Sequence; Kidney Cysts Segmentation in CT Images; Audio Visual Attention Models in Mobile Robots Navigation; Local Adaptive Image Processing; Learning Techniques for Intelligent Access Control; Resolution Improvement in Acoustic Maps. Each chapter is self-contained with its own references. Some of the chapters are devoted to the theoretical aspects while the others are presenting the practical aspects and the analysis of the modeling of the developed algorithms in different application areas.
Author: Milan Hájek
Publisher: Texture Analysis Magn Resona
ISBN: 9788090366008
Category : Magnetic resonance imaging
Languages : en
Pages : 248
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Book Description
Author: Sankar K. Pal
Publisher: CRC Press
ISBN: 1439803307
Category : Computers
Languages : en
Pages : 259
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Book Description
Fuzzy sets, near sets, and rough sets are useful and important stepping stones in a variety of approaches to image analysis. These three types of sets and their various hybridizations provide powerful frameworks for image analysis. Emphasizing the utility of fuzzy, near, and rough sets in image analysis, Rough Fuzzy Image Analysis: Foundations and
Author: Hamid R. Arabnia
Publisher: Springer Nature
ISBN: 3030702960
Category : Technology & Engineering
Languages : en
Pages : 1152
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Book Description
The book presents the proceedings of two conferences: The 22nd International Conference on Artificial Intelligence (ICAI’20) and The 4th International Conference on Applied Cognitive Computing (ACC’20). The conferences took place in Las Vegas, NV, USA, July 27-30, 2020, and are part of the larger 2020 World Congress in Computer Science, Computer Engineering, & Applied Computing (CSCE'20), which features 20 major tracks. Topics include: deep learning; neural networks; brain models; cognitive science; natural language processing; fuzzy logic and soft computing (ICAI) and novel computationally intelligent algorithms; bio inspired cognitive algorithms; modeling human brain processing systems (ACC); and more. Authors include academics, researchers, and professionals. Presents the proceedings of two conferences as part of the 2020 World Congress in Computer Science, Computer Engineering, & Applied Computing (CSCE'20); Includes the tracks: artificial intelligence and applied cognitive computing; Features papers from the 22nd International Conference on AI (ICAI’20) and the 4th International Conference on Applied Cognitive Computing (ACC’20).
Author: Tshilidzi Marwala
Publisher: Springer Science & Business Media
ISBN: 1447123794
Category : Technology & Engineering
Languages : en
Pages : 247
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Book Description
Condition Monitoring Using Computational Intelligence Methods promotes the various approaches gathered under the umbrella of computational intelligence to show how condition monitoring can be used to avoid equipment failures and lengthen its useful life, minimize downtime and reduce maintenance costs. The text introduces various signal-processing and pre-processing techniques, wavelets and principal component analysis, for example, together with their uses in condition monitoring and details the development of effective feature extraction techniques classified into frequency-, time-frequency- and time-domain analysis. Data generated by these techniques can then be used for condition classification employing tools such as: • fuzzy systems; rough and neuro-rough sets; neural and Bayesian networks;hidden Markov and Gaussian mixture models; and support vector machines.
Author: De-Shuang Huang
Publisher: Springer Science & Business Media
ISBN: 3642149316
Category : Computers
Languages : en
Pages : 701
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Book Description
The International Conference on Intelligent Computing (ICIC) was formed to provide an annual forum dedicated to the emerging and challenging topics in artificial intel- gence, machine learning, pattern recognition, image processing, bioinformatics, and computational biology. It aims to bring together researchers and practitioners from both academia and industry to share ideas, problems, and solutions related to the m- tifaceted aspects of intelligent computing. ICIC 2010, held in Changsha, China, August 18–21, 2010, constituted the 6th - ternational Conference on Intelligent Computing. It built upon the success of ICIC 2009, ICIC 2008, ICIC 2007, ICIC 2006, and ICIC 2005, that were held in Ulsan, Korea, Shanghai, Qingdao, Kunming, and Hefei, China, respectively. This year, the conference concentrated mainly on the theories and methodologies as well as the emerging applications of intelligent computing. Its aim was to unify the picture of contemporary intelligent computing techniques as an integral concept that highlights the trends in advanced computational intelligence and bridges theoretical research with applications. Therefore, the theme for this conference was “Advanced Intelligent Computing Technology and Applications.” Papers focusing on this theme were solicited, addressing theories, methodologies, and applications in science and technology.
Author: Prateek Singhal
Publisher: CRC Press
ISBN: 1000822958
Category : Computers
Languages : en
Pages : 321
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Book Description
There is presently a drastic growth in multimedia data. During the Covid-19 pandemic, we observed that images helped doctors immensely in the rapid detection of Covid-19 infection in patients. There are many critical applications in which images play a vital role. These applications use raw image data to extract some useful information about the world around us. The quick extraction of valuable information from raw images is one challenge that academicians and professionals face in the present day. This is where image processing comes into action. Image processing’s primary purpose is to get an enhanced image or extract some useful information from raw image data. Therefore, there is a major need for some technique or system that addresses this challenge. Intelligent Systems have emerged as a solution to address quick image information extraction. In simple words, an Intelligent System can be defined as a mathematical model that adapts itself to deal with a problem’s dynamicity. These systems learn how to act so an image can reach an objective. An Intelligent System helps accomplish various image-processing functions like enhancement, segmentation, reconstruction, object detection, and morphing. The advent of Intelligent Systems in the image-processing field has leveraged many critical applications for humankind. These critical applications include factory automation, biomedical imaging analysis, decision econometrics, as well as related challenges.
