An optimal approach to unsupervised colour image clustering is presented in this research which is suited for high resolution images based on mode seeking by mediod shifts. It is shown that automatic detection of total number of clusters depends upon overall image statistics as well as the bandwidth of the underlying probability density function. An optimized adaptive mode seeking algorithm based on reverse parallel tree traversal is proposed. This work has contribution in three aspects. 1) Adaptive bandwidth for kernel function is proposed; 2) A novel reverse parallel tree traversing approach for mode seeking is presented; 3) For high resolution images block clustering based optimized Adaptive Mediod Shift (AMS) is proposed. The proposed method has made it possible to perform clustering on variety of high resolution images. The proposed method is applied to automated glacier segmentation from 6 band Landsat TM sensor satellite images of Hindukush and KaraKoram mountain ranges of Asia. The method along with other proposed techniques successfully delineates the glaciers into class Clean Glacier and class Debris Covered Glacier.
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Syed Zulqarnain Gilani did his Bachelor in Engineering and Masters in Electrical Engineering from National University of Sciences and Technology, Pakistan. His research interests include clustering and segmentation besides wireless communication. He has a number of publications in world reputed conferences
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -An optimal approach to unsupervised colour image clustering is presented in this research which is suited for high resolution images based on mode seeking by mediod shifts. It is shown that automatic detection of total number of clusters depends upon overall image statistics as well as the bandwidth of the underlying probability density function. An optimized adaptive mode seeking algorithm based on reverse parallel tree traversal is proposed. This work has contribution in three aspects. 1) Adaptive bandwidth for kernel function is proposed; 2) A novel reverse parallel tree traversing approach for mode seeking is presented; 3) For high resolution images block clustering based optimized Adaptive Mediod Shift (AMS) is proposed. The proposed method has made it possible to perform clustering on variety of high resolution images. The proposed method is applied to automated glacier segmentation from 6 band Landsat TM sensor satellite images of Hindukush and KaraKoram mountain ranges of Asia. The method along with other proposed techniques successfully delineates the glaciers into class Clean Glacier and class Debris Covered Glacier. 136 pp. Englisch. Seller Inventory # 9783844386264
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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Gilani Syed Zulqarnain AhmadSyed Zulqarnain Gilani did his Bachelor in Engineering and Masters in Electrical Engineering from National University of Sciences and Technology, Pakistan. His research interests include clustering and seg. Seller Inventory # 5476144
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Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - An optimal approach to unsupervised colour image clustering is presented in this research which is suited for high resolution images based on mode seeking by mediod shifts. It is shown that automatic detection of total number of clusters depends upon overall image statistics as well as the bandwidth of the underlying probability density function. An optimized adaptive mode seeking algorithm based on reverse parallel tree traversal is proposed. This work has contribution in three aspects. 1) Adaptive bandwidth for kernel function is proposed; 2) A novel reverse parallel tree traversing approach for mode seeking is presented; 3) For high resolution images block clustering based optimized Adaptive Mediod Shift (AMS) is proposed. The proposed method has made it possible to perform clustering on variety of high resolution images. The proposed method is applied to automated glacier segmentation from 6 band Landsat TM sensor satellite images of Hindukush and KaraKoram mountain ranges of Asia. The method along with other proposed techniques successfully delineates the glaciers into class Clean Glacier and class Debris Covered Glacier. Seller Inventory # 9783844386264
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Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -An optimal approach to unsupervised colour image clustering is presented in this research which is suited for high resolution images based on mode seeking by mediod shifts. It is shown that automatic detection of total number of clusters depends upon overall image statistics as well as the bandwidth of the underlying probability density function. An optimized adaptive mode seeking algorithm based on reverse parallel tree traversal is proposed. This work has contribution in three aspects. 1) Adaptive bandwidth for kernel function is proposed; 2) A novel reverse parallel tree traversing approach for mode seeking is presented; 3) For high resolution images block clustering based optimized Adaptive Mediod Shift (AMS) is proposed. The proposed method has made it possible to perform clustering on variety of high resolution images. The proposed method is applied to automated glacier segmentation from 6 band Landsat TM sensor satellite images of Hindukush and KaraKoram mountain ranges of Asia. The method along with other proposed techniques successfully delineates the glaciers into class Clean Glacier and class Debris Covered Glacier.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 136 pp. Englisch. Seller Inventory # 9783844386264
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Taschenbuch. Condition: Neu. Automated Glacier Segmentation By Fast Adaptive Medoid Shift Algorithm | Segmentation of Glaciers using Digital Elevation Model and Fast Block Clustering Based Adaptive Medoid Shift Algorithm | Syed Zulqarnain Ahmad Gilani | Taschenbuch | 136 S. | Englisch | 2011 | LAP LAMBERT Academic Publishing | EAN 9783844386264 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu. Seller Inventory # 106824441
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