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This Book contributes analysis and development of image segmentation algorithms based on finite logistic type mixture models. These techniques are much useful in a variety of applications such as medical images, filming, and video, security surveillance, face recognition, gesture analysis. Image segmentation is a prerequisite for computer vision and human-computer interactions. Image segmentation is an important domain of research in computer science and allied areas due to its ready applicability in designing and developing several systems. The image segmentation is a process in which the pixels in the image are grouped such that they form a number of meaningful regions that are homogeneous within the regions, heterogeneous between the regions. Several image segmentation techniques have been developed with various considerations. A comparative study is carried with developed algorithms and with earlier existing models based on image segmentation algorithm with Gaussian mixture model. It is observed that the three-parameter logistic type mixture model with hierarchical clustering algorithm better than that of a Gaussian mixture model with K-means and two-parameter logistic type.
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Segmentation Methods Based On Logistic Type Mixture Model
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LAP Lambert Academic Publishing 2020-12, 2020
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ISBN 13: 9786203199048
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Segmentation Methods Based On Logistic Type Mixture Model
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Segmentation Methods Based On Logistic Type Mixture Model
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Segmentation Methods Based On Logistic Type Mixture Model
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Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This Book contributes analysis and development of image segmentation algorithms based on finite logistic type mixture models. These techniques are much useful in a variety of applications such as medical images, filming, and video, security surveillance, face recognition, gesture analysis. Image segmentation is a prerequisite for computer vision and human-computer interactions. Image segmentation is an important domain of research in computer science and allied areas due to its ready applicability in designing and developing several systems. The image segmentation is a process in which the pixels in the image are grouped such that they form a number of meaningful regions that are homogeneous within the regions, heterogeneous between the regions. Several image segmentation techniques have been developed with various considerations. A comparative study is carried with developed algorithms and with earlier existing models based on image segmentation algorithm with Gaussian mixture model. It is observed that the three-parameter logistic type mixture model with hierarchical clustering algorithm better than that of a Gaussian mixture model with K-means and two-parameter logistic type. 188 pp. Englisch. Codice articolo 9786203199048
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Segmentation Methods Based On Logistic Type Mixture Model
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Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Kalahasthi Venkata SatyanarayanaDr.K.VENKATA SATYANARAYANA is currently working as an Associate Professor in the Department of CSE, Raghu Engineering College, AP, India. PROF.K.SRINIVASA RAO is working as The Principal, College of Sc. Codice articolo 452575881
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Segmentation Methods Based On Logistic Type Mixture Model
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LAP LAMBERT Academic Publishing, 2020
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Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This Book contributes analysis and development of image segmentation algorithms based on finite logistic type mixture models. These techniques are much useful in a variety of applications such as medical images, filming, and video, security surveillance, face recognition, gesture analysis. Image segmentation is a prerequisite for computer vision and human-computer interactions. Image segmentation is an important domain of research in computer science and allied areas due to its ready applicability in designing and developing several systems. The image segmentation is a process in which the pixels in the image are grouped such that they form a number of meaningful regions that are homogeneous within the regions, heterogeneous between the regions. Several image segmentation techniques have been developed with various considerations. A comparative study is carried with developed algorithms and with earlier existing models based on image segmentation algorithm with Gaussian mixture model. It is observed that the three-parameter logistic type mixture model with hierarchical clustering algorithm better than that of a Gaussian mixture model with K-means and two-parameter logistic type. Codice articolo 9786203199048
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Segmentation Methods Based On Logistic Type Mixture Model
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ISBN 10: 6203199044
ISBN 13: 9786203199048
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Segmentation Methods Based On Logistic Type Mixture Model
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ISBN 10: 6203199044
ISBN 13: 9786203199048
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