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Image Classification- Based on Fuzzy C means Clustering Algorithm: Sub pixel classification using Remote sensed data - Softcover

 
9783659953187: Image Classification- Based on Fuzzy C means Clustering Algorithm: Sub pixel classification using Remote sensed data

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The analysis of Fuzzy Logic is carried out by varying the number of classes and also by changing the number of classes per pixel. Different classification methods yields different results and none of the methods is suitable for variable classes and variable pixels. Depending upon the information needed about the classification, suitable classes and suitable classes per pixel should be selected. The selection of a particular method is dependent on number of classes and number of classes per pixel. The suitability of a particular scheme depends to some extent on the nature of the image to be classified. When results of all the classified methods considered were compared, application of Fuzzy Logic only makes the classification more complex. It is because of the type of the data used for classification. Since the data used is a 23.5m resolution data, which is considered as low resolution data, almost all the methods produce reasonably high accuracy value. It is hard to come to a conclusion by visually examining the classified images. Hence an accuracy assessment is carried out for numerically/quantitatively finding the classification method that results in highest accuracy value.

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The analysis of Fuzzy Logic is carried out by varying the number of classes and also by changing the number of classes per pixel. Different classification methods yields different results and none of the methods is suitable for variable classes and variable pixels. Depending upon the information needed about the classification, suitable classes and suitable classes per pixel should be selected. The selection of a particular method is dependent on number of classes and number of classes per pixel. The suitability of a particular scheme depends to some extent on the nature of the image to be classified. When results of all the classified methods considered were compared, application of Fuzzy Logic only makes the classification more complex. It is because of the type of the data used for classification. Since the data used is a 23.5m resolution data, which is considered as low resolution data, almost all the methods produce reasonably high accuracy value. It is hard to come to a conclusion by visually examining the classified images. Hence an accuracy assessment is carried out for numerically/quantitatively finding the classification method that results in highest accuracy value.

Biografía del autor

Jayanth J has received M.Tech from MCE, Hassan in 2010,Pursuing Ph.D, VTU. He is working as Associate Professor in the Dept.of ECE,GSSSIETW, Mysuru.He is in teaching for 6 years. His subjects of interest include Image Processing, Fuzzy Logic, Remote Sensing & Swarm Intelligence

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Zustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: J. JayanthJayanth J has received M.Tech from MCE, Hassan in 2010,Pursuing Ph.D, VTU. He is working as Associate Professor in the Dept.of ECE,GSSSIETW, Mysuru.He is in teaching for 6 years. His subjects of interest include Image Proce. Bestandsnummer des Verkäufers 158878106

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Taschenbuch. Zustand: Neu. Neuware -The analysis of Fuzzy Logic is carried out by varying the number of classes and also by changing the number of classes per pixel. Different classification methods yields different results and none of the methods is suitable for variable classes and variable pixels. Depending upon the information needed about the classification, suitable classes and suitable classes per pixel should be selected. The selection of a particular method is dependent on number of classes and number of classes per pixel. The suitability of a particular scheme depends to some extent on the nature of the image to be classified. When results of all the classified methods considered were compared, application of Fuzzy Logic only makes the classification more complex. It is because of the type of the data used for classification. Since the data used is a 23.5m resolution data, which is considered as low resolution data, almost all the methods produce reasonably high accuracy value. It is hard to come to a conclusion by visually examining the classified images. Hence an accuracy assessment is carried out for numerically/quantitatively finding the classification method that results in highest accuracy value.Books on Demand GmbH, Überseering 33, 22297 Hamburg 156 pp. Englisch. Bestandsnummer des Verkäufers 9783659953187

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Taschenbuch. Zustand: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - The analysis of Fuzzy Logic is carried out by varying the number of classes and also by changing the number of classes per pixel. Different classification methods yields different results and none of the methods is suitable for variable classes and variable pixels. Depending upon the information needed about the classification, suitable classes and suitable classes per pixel should be selected. The selection of a particular method is dependent on number of classes and number of classes per pixel. The suitability of a particular scheme depends to some extent on the nature of the image to be classified. When results of all the classified methods considered were compared, application of Fuzzy Logic only makes the classification more complex. It is because of the type of the data used for classification. Since the data used is a 23.5m resolution data, which is considered as low resolution data, almost all the methods produce reasonably high accuracy value. It is hard to come to a conclusion by visually examining the classified images. Hence an accuracy assessment is carried out for numerically/quantitatively finding the classification method that results in highest accuracy value. Bestandsnummer des Verkäufers 9783659953187

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Taschenbuch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The analysis of Fuzzy Logic is carried out by varying the number of classes and also by changing the number of classes per pixel. Different classification methods yields different results and none of the methods is suitable for variable classes and variable pixels. Depending upon the information needed about the classification, suitable classes and suitable classes per pixel should be selected. The selection of a particular method is dependent on number of classes and number of classes per pixel. The suitability of a particular scheme depends to some extent on the nature of the image to be classified. When results of all the classified methods considered were compared, application of Fuzzy Logic only makes the classification more complex. It is because of the type of the data used for classification. Since the data used is a 23.5m resolution data, which is considered as low resolution data, almost all the methods produce reasonably high accuracy value. It is hard to come to a conclusion by visually examining the classified images. Hence an accuracy assessment is carried out for numerically/quantitatively finding the classification method that results in highest accuracy value. 156 pp. Englisch. Bestandsnummer des Verkäufers 9783659953187

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