Image Classification of Single Layered Cloud Types

Language: English

Published by LAP LAMBERT Academic Publishing Apr 2011, 2011

3844328262 / 9783844328264

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Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermanyBuchWeltWeit Ludwig Meier e.K.

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Softcover

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This item is printed on demand - it takes 3-4 days longer - Neuware -An automatic classification system is presented, which discriminates the different types of single- layered clouds using Principal Component Analysis (PCA) with enhanced accuracy and provides fast processing speed as compared to other techniques. The system is first trained by cloud images. In training phase, system reads major principal features of the different cloud images to produce an image space. In testing phase, a new cloud image can be classified by comparing it with the specified image space using the PCA algorithm. Weather forecasting applications use various pattern recognition techniques to analyze clouds' information and other meteorological parameters. Neural Networks is an often-used methodology for image processing. Some statistical methodologies like FDA, RBFNN and SVM are also being used for image analysis. These methodologies require more training time and have limited accuracy of about 70%. This level of accuracy often degrades classification of clouds, and hence the accuracy of rain and other weather predictions is reduced. PCA algorithm provides a more accurate cloud classification that yield better and concise forecasting of rain. 80 pp. Englisch.…

Seller Inventory # 9783844328264

Title
Image Classification of Single Layered Cloud Types
Author
Imran Sarwar Bajwa
Publisher
LAP LAMBERT Academic Publishing Apr 2011
Publication year
2011
Condition
Neu
Binding
Taschenbuch
Language
English
ISBN 10
3844328262
ISBN 13
9783844328264
Item weight
137 grams
Dimensions
220x150x5 mm

BuchWeltWeit Ludwig Meier e.K.

Bergisch Gladbach, Germany

5-star seller

AbeBooks seller since January 11, 2012

Shipping rates from Germany to U.S.A.

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BuchWeltWeit Ludwig Meier e.K.

Germany