Image Classification Based Fuzzy by Jayanth (9 results)

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Paperback. Condition: Brand New. 156 pages. 8.66x5.91x0.36 inches. In Stock.

Taschenbuch. Condition: Neu. Image Classification- Based on Fuzzy C means Clustering Algorithm | Sub pixel classification using Remote sensed data | Jayanth J. | Taschenbuch | 156 S. | Englisch | 2016 | LAP LAMBERT Academic Publishing | EAN 9783659953187 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.

Taschenbuch. Condition: 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.

Condition: 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.

Condition: New. Print on Demand.

Condition: New. PRINT ON DEMAND.

Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. 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.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 156 pp. Englisch.

Taschenbuch. Condition: 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.