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Author: Eser Sert
Publisher: Infinite Study
ISBN:
Category :
Languages : en
Pages : 17
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Book Description
Segmentation is paramount to 3D video systems employing multi-view video-plus-depth data (MVD) to implement free-viewpoint navigation and comfortable 3D viewing, modeling, and comprehension.
Author: Eser Sert
Publisher: Infinite Study
ISBN:
Category :
Languages : en
Pages : 17
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Book Description
Segmentation is paramount to 3D video systems employing multi-view video-plus-depth data (MVD) to implement free-viewpoint navigation and comfortable 3D viewing, modeling, and comprehension.
Author: Mohammad Naved Qureshi
Publisher: Infinite Study
ISBN:
Category :
Languages : en
Pages : 7
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Book Description
Images are one of the primary media for sharing information. The image segmentation is an important image processing approach, which analyzes what is inside the image. Image segmentation can be used in content-based image retrieval, image feature extraction, pattern recognition, etc. In this work, clustering based image segmentation method used and modified by introducing neutrosophic logic.
Author: Shaima Elnazer
Publisher: Infinite Study
ISBN:
Category :
Languages : en
Pages : 7
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Book Description
Abstract: an improved segmentation approach based on Neutrosophic sets (NS) and Modified Non local Fuzzy c-mean clustering (NLFCM) is proposed. The brain tumor MRI image is transformed into NS domain, which is described using three subsets namely; the percentage of truth in a subset T% , the percentage of indeterminacy in a subset I% , and the percentage of falsity in a subset F% . The entropy in NS is defined and employed to evaluate the indeterminacy.
Author: Xindong Peng
Publisher: Infinite Study
ISBN:
Category : Mathematics
Languages : en
Pages : 57
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Book Description
Neutrosophic set, initiated by Smarandache, is a novel tool to deal with vagueness considering the truth-membership T , indeterminacy-membership I and falsity-membership F satisfying the condition 0 ≤ T + I + F ≤ 3. It can be used to characterize the uncertain information more sufficiently and accurately than intuitionistic fuzzy set. Neutrosophic set has attracted great attention of many scholars that have been extended to new types and these extensions have been used in many areas such as aggregation operators, decision making, image processing, information measures, graph and algebraic structures. Because of such a growth, we present an overview on neutrosophic set with the aim of offering a clear perspective on the different concepts, tools and trends related to their extensions. A total of 137 neutrosophic set publication records from Web of Science are analyzed. Many interesting results with regard to the annual trends, the top players in terms of country level as well as institutional level, the publishing journals, the highly cited papers, and the research landscape are yielded and explained in-depth. The results indicate that some developing economics (such as China, India, Turkey) are quite active in neutrosophic set research. Moreover, the co-authorship analysis of the country and institution, the co-citation analysis of the journal, reference and author, and the co-occurrence analysis of the keywords are presented byVOSviewer software.
Author: Florentin Smarandache
Publisher: Infinite Study
ISBN:
Category :
Languages : en
Pages : 210
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Book Description
This Special Issue presents original research papers that report on state-of-the-art and recent advancements in neutrosophic sets and logic in soft computing, artificial intelligence, big and small data mining, decision making problems, and practical achievements.
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: Amira S. Ashour
Publisher: Infinite Study
ISBN:
Category : Mathematics
Languages : en
Pages : 8
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Book Description
Dermoscopic images suffer from irregular and vague boundaries. New directions established the neutrosophic set (NS) approaches for clustering, and segmenting the dermoscopic images. In this work, an accurate segmentation process was developed by mapping initially the dermoscopic images to the NS domain. Thus, the neutrosophic image was defined by three subsets, namely True (T ), Indeterminacy (I) and False (F). For accurate boundary detection and segmentation, different high pass (HP) filter types were used in the definition of I subset and low pass (LP) filter types in the definition of T .
Author: Eser SERT
Publisher: Infinite Study
ISBN:
Category : Mathematics
Languages : en
Pages : 13
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Book Description
In this study, a new edge detection method based on Neutrosophic Set (NS) struc- ture via using maximum norm entropy (EDA-MNE) is proposed.
Author: DEEPIKA KOUNDAL
Publisher: Infinite Study
ISBN:
Category :
Languages : en
Pages : 19
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Book Description
In medical science, diagnosis and prognosis is one of the most difficult and challenging task because of restricted subjectivity of the experts and presence of fuzziness in medical images. In observing the severity of several diseases, different professional experts may result in wrong diagnosis. In order to perform diagnosis intuitively in the medical images, different image processing methods have been explored in terms of neutrosophic theory to interpret the inherent uncertainty, ambiguity and vagueness. This paper demonstrates the use of neutrosophic theory in medical image denoising and segmentation where the performance is observed to be much better.
Author: Florentin Smarandache