Design of Unsupervised Learning for Automatic Segmentation: Medical Image Segmentation - Tapa blanda

Kumar, B. Suresh

9786200224668: Design of Unsupervised Learning for Automatic Segmentation: Medical Image Segmentation

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ISBN 10: 6200224668 ISBN 13: 9786200224668

Editorial: LAP LAMBERT Academic Publishing, 2019

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The image segmentation is used to change or simplify the image representation for the purpose of easy understanding or quicker analysis. Image segmentation is a process of segmenting an image into groups of pixels based on some criterions. Image segmentation is the process of partitioning a digital image into multiple segments. The purpose of image segmentation is to partition an image into meaningful regions with respect to particular application. The image segmentation is used for various applications such as medical images, Satellite images, content based image retrieval, machine vision, Recognition Tasks and Video Surveillance. There are so many methods used for segmentations such as compression based methods, thresholding, and clustering. The clustering methods can be divided into two parts namely supervised and unsupervised. Supervised clustering involves predefining the cluster size for segmenting whereas unsupervised segmentation segments by its own cluster values.

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Editorial: LAP LAMBERT Academic Publishing
A�o de publicaci�n: 2019
Idioma: Ingl�s
ISBN 10: 6200224668
ISBN 13: 9786200224668
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Design of Unsupervised Learning for Automatic Segmentation

B. Suresh Kumar

Publicado por LAP LAMBERT Academic Publishing, 2019

ISBN 10: 6200224668 ISBN 13: 9786200224668

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Condici�n: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Kumar B. SureshMr.B.Suresh Kumar is doing Ph.D in Computer Science at Karpagam University, Coimbatore-21. He obtained M.Phil in Computer Science from Manonmaniam Sundaranar University, in 2003 and M.Sc. in Computer Science from Bhara. N� de ref. del art�culo: 385885527

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Design of Unsupervised Learning for Automatic Segmentation

B. Suresh Kumar

Publicado por LAP LAMBERT Academic Publishing Jul 2019, 2019

ISBN 10: 6200224668 ISBN 13: 9786200224668

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Taschenbuch. Condici�n: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The image segmentation is used to change or simplify the image representation for the purpose of easy understanding or quicker analysis. Image segmentation is a process of segmenting an image into groups of pixels based on some criterions. Image segmentation is the process of partitioning a digital image into multiple segments. The purpose of image segmentation is to partition an image into meaningful regions with respect to particular application. The image segmentation is used for various applications such as medical images, Satellite images, content based image retrieval, machine vision, Recognition Tasks and Video Surveillance. There are so many methods used for segmentations such as compression based methods, thresholding, and clustering. The clustering methods can be divided into two parts namely supervised and unsupervised. Supervised clustering involves predefining the cluster size for segmenting whereas unsupervised segmentation segments by its own cluster values. 136 pp. Englisch. N� de ref. del art�culo: 9786200224668

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Design of Unsupervised Learning for Automatic Segmentation : Medical Image Segmentation

B. Suresh Kumar

Publicado por LAP LAMBERT Academic Publishing, 2019

ISBN 10: 6200224668 ISBN 13: 9786200224668

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Taschenbuch. Condici�n: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - The image segmentation is used to change or simplify the image representation for the purpose of easy understanding or quicker analysis. Image segmentation is a process of segmenting an image into groups of pixels based on some criterions. Image segmentation is the process of partitioning a digital image into multiple segments. The purpose of image segmentation is to partition an image into meaningful regions with respect to particular application. The image segmentation is used for various applications such as medical images, Satellite images, content based image retrieval, machine vision, Recognition Tasks and Video Surveillance. There are so many methods used for segmentations such as compression based methods, thresholding, and clustering. The clustering methods can be divided into two parts namely supervised and unsupervised. Supervised clustering involves predefining the cluster size for segmenting whereas unsupervised segmentation segments by its own cluster values. N� de ref. del art�culo: 9786200224668

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Design of Unsupervised Learning for Automatic Segmentation: Medical Image Segmentation

Kumar, B. Suresh

Publicado por LAP LAMBERT Academic Publishing, 2019

ISBN 10: 6200224668 ISBN 13: 9786200224668

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Design of Unsupervised Learning for Automatic Segmentation: Medical Image Segmentation

Kumar, B. Suresh

Publicado por LAP LAMBERT Academic Publishing, 2019

ISBN 10: 6200224668 ISBN 13: 9786200224668

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Design of Unsupervised Learning for Automatic Segmentation

B. Suresh Kumar

Publicado por LAP LAMBERT Academic Publishing Jul 2019, 2019

ISBN 10: 6200224668 ISBN 13: 9786200224668

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Taschenbuch. Condici�n: Neu. Neuware -The image segmentation is used to change or simplify the image representation for the purpose of easy understanding or quicker analysis. Image segmentation is a process of segmenting an image into groups of pixels based on some criterions. Image segmentation is the process of partitioning a digital image into multiple segments. The purpose of image segmentation is to partition an image into meaningful regions with respect to particular application. The image segmentation is used for various applications such as medical images, Satellite images, content based image retrieval, machine vision, Recognition Tasks and Video Surveillance. There are so many methods used for segmentations such as compression based methods, thresholding, and clustering. The clustering methods can be divided into two parts namely supervised and unsupervised. Supervised clustering involves predefining the cluster size for segmenting whereas unsupervised segmentation segments by its own cluster values.Books on Demand GmbH, �berseering 33, 22297 Hamburg 136 pp. Englisch. N� de ref. del art�culo: 9786200224668

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