METHODS AND SYSTEMS FOR PERFORMING SEGMENTATION AND REGISTRATION OF IMAGES USING NEUTROSOPHIC SIMILARITY SCORES PDF Download
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Author: Yanhui Guo
Publisher: Infinite Study
ISBN:
Category : Mathematics
Languages : en
Pages : 22
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Book Description
An example method for segmenting an object contained in an image includes receiving an image including a plurality of pixels , transforming a plurality of characteristics of a pixel into respective neutrosophic set domains , calculating a neutrosophic similarity score for the pixel based on the respective neutrosophic set domains for the characteristics of the pixel , segmenting an object from background of the image using a region growing algorithm based on the neutrosophic similarity score for the pixel , and receiving a margin adjustment related to the object segmented from the background of the image .
Author: Yanhui Guo
Publisher: Infinite Study
ISBN:
Category : Mathematics
Languages : en
Pages : 22
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Book Description
An example method for segmenting an object contained in an image includes receiving an image including a plurality of pixels , transforming a plurality of characteristics of a pixel into respective neutrosophic set domains , calculating a neutrosophic similarity score for the pixel based on the respective neutrosophic set domains for the characteristics of the pixel , segmenting an object from background of the image using a region growing algorithm based on the neutrosophic similarity score for the pixel , and receiving a margin adjustment related to the object segmented from the background of the image .
Author: Florentin Smarandache
Publisher: Infinite Study
ISBN:
Category : Mathematics
Languages : en
Pages : 10
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Book Description
In this paper one generalizes the intuitionistic fuzzy set (IFS), paraconsistent set, and intuitionistic set to the neutrosophic set (NS). Many examples are presented. Distinctions between NS and IFS are underlined.
Author: Mark Nixon
Publisher: Academic Press
ISBN: 0123978246
Category : Computers
Languages : en
Pages : 629
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Book Description
Feature Extraction and Image Processing for Computer Vision is an essential guide to the implementation of image processing and computer vision techniques, with tutorial introductions and sample code in Matlab. Algorithms are presented and fully explained to enable complete understanding of the methods and techniques demonstrated. As one reviewer noted, "The main strength of the proposed book is the exemplar code of the algorithms." Fully updated with the latest developments in feature extraction, including expanded tutorials and new techniques, this new edition contains extensive new material on Haar wavelets, Viola-Jones, bilateral filtering, SURF, PCA-SIFT, moving object detection and tracking, development of symmetry operators, LBP texture analysis, Adaboost, and a new appendix on color models. Coverage of distance measures, feature detectors, wavelets, level sets and texture tutorials has been extended. - Named a 2012 Notable Computer Book for Computing Methodologies by Computing Reviews - Essential reading for engineers and students working in this cutting-edge field - Ideal module text and background reference for courses in image processing and computer vision - The only currently available text to concentrate on feature extraction with working implementation and worked through derivation
Author: Florentin Smarandache
Publisher: Academic Press
ISBN: 0128199083
Category : Mathematics
Languages : en
Pages : 448
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Book Description
Optimization Theory Based on Neutrosophic and Plithogenic Sets presents the state-of-the-art research on neutrosophic and plithogenic theories and their applications in various optimization fields. Its table of contents covers new concepts, methods, algorithms, modelling, and applications of green supply chain, inventory control problems, assignment problems, transportation problem, nonlinear problems and new information related to optimization for the topic from the theoretical and applied viewpoints in neutrosophic sets and logic. - All essential topics about neutrosophic optimization and Plithogenic sets make this volume the only single source of comprehensive information - New and innovative theories help researchers solve problems under diverse optimization environments - Varied applications address practitioner fields such as computational intelligence, image processing, medical diagnosis, fault diagnosis, and optimization design
Author: Yanhui Guo
Publisher: Academic Press
ISBN: 0128181494
Category : Computers
Languages : en
Pages : 372
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Book Description
Neutrosophic Set in Medical Image Analysis gives an understanding of the concepts of NS, along with knowledge on how to gather, interpret, analyze and handle medical images using NS methods. It presents the latest cutting-edge research that gives insight into neutrosophic set's novel techniques, strategies and challenges, showing how it can be used in biomedical diagnoses systems. The neutrosophic set (NS), which is a generalization of fuzzy set, offers the prospect of overcoming the restrictions of fuzzy-based approaches to medical image analysis. - Introduces the mathematical model and concepts of neutrosophic theory and methods - Highlights the different techniques of neutrosophic theory, focusing on applying the neutrosophic set in image analysis to support computer- aided diagnosis (CAD) systems, including approaches from soft computing and machine learning - Shows how NS techniques can be applied to medical image denoising, segmentation and classification - Provides challenges and future directions in neutrosophic set based medical image analysis
Author: Oliver Ibe
Publisher: Newnes
ISBN: 0124078397
Category : Mathematics
Languages : en
Pages : 515
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Book Description
Markov processes are processes that have limited memory. In particular, their dependence on the past is only through the previous state. They are used to model the behavior of many systems including communications systems, transportation networks, image segmentation and analysis, biological systems and DNA sequence analysis, random atomic motion and diffusion in physics, social mobility, population studies, epidemiology, animal and insect migration, queueing systems, resource management, dams, financial engineering, actuarial science, and decision systems. Covering a wide range of areas of application of Markov processes, this second edition is revised to highlight the most important aspects as well as the most recent trends and applications of Markov processes. The author spent over 16 years in the industry before returning to academia, and he has applied many of the principles covered in this book in multiple research projects. Therefore, this is an applications-oriented book that also includes enough theory to provide a solid ground in the subject for the reader. - Presents both the theory and applications of the different aspects of Markov processes - Includes numerous solved examples as well as detailed diagrams that make it easier to understand the principle being presented - Discusses different applications of hidden Markov models, such as DNA sequence analysis and speech analysis.
Author: Janmenjoy Nayak
Publisher: Academic Press
ISBN: 0128222611
Category : Science
Languages : en
Pages : 398
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Book Description
Handbook of Computational Intelligence in Biomedical Engineering and Healthcare helps readers analyze and conduct advanced research in specialty healthcare applications surrounding oncology, genomics and genetic data, ontologies construction, bio-memetic systems, biomedical electronics, protein structure prediction, and biomedical data analysis. The book provides the reader with a comprehensive guide to advanced computational intelligence, spanning deep learning, fuzzy logic, connectionist systems, evolutionary computation, cellular automata, self-organizing systems, soft computing, and hybrid intelligent systems in biomedical and healthcare applications. Sections focus on important biomedical engineering applications, including biosensors, enzyme immobilization techniques, immuno-assays, and nanomaterials for biosensors and other biomedical techniques. Other sections cover gene-based solutions and applications through computational intelligence techniques and the impact of nonlinear/unstructured data on experimental analysis. - Presents a comprehensive handbook that covers an Introduction to Computational Intelligence in Biomedical Engineering and Healthcare, Computational Intelligence Techniques, and Advanced and Emerging Techniques in Computational Intelligence - Helps readers analyze and do advanced research in specialty healthcare applications - Includes links to websites, videos, articles and other online content to expand and support primary learning objectives
Author: Harish Garg
Publisher: Springer Nature
ISBN: 9811619891
Category : Mathematics
Languages : en
Pages : 443
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Book Description
This book presents a collection of recent research on topics related to Pythagorean fuzzy set, dealing with dynamic and complex decision-making problems. It discusses a wide range of theoretical and practical information to the latest research on Pythagorean fuzzy sets, allowing readers to gain an extensive understanding of both fundamentals and applications. It aims at solving various decision-making problems such as medical diagnosis, pattern recognition, construction problems, technology selection, and more, under the Pythagorean fuzzy environment, making it of much value to students, researchers, and professionals associated with the field.
Author: Juri Yanase
Publisher: Infinite Study
ISBN:
Category : Mathematics
Languages : en
Pages : 51
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Book Description
Computer-aided diagnosis (CAD) in medicine is the result of a large amount of effort expended in the interface of medicine and computer science. As some CAD systems in medicine try to emulate the diagnostic decision-making process of medical experts, they can be considered as expert systems in medicine.
Author: Florentin Smarandache
Publisher:
ISBN:
Category : Mathematics
Languages : en
Pages : 110
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Book Description
