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Viac informácií o knihe Using Multiple Robust Parameter Design Techniques to Improve Hyperspectral Anomaly Detection Algorithm Performance

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• Anotácia kniha
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Anotácia knihy

Detecting and identifying objects of interest is the goal of all remote sensing. New advances, specifically in hyperspectral imaging technology have provided the analyst with immense amounts of data requiring evaluation. Several filtering techniques or anomaly detection algorithms have been proposed. However, most new algorithms are insuciently verified to be robust to the broad range of hyperspectral data being made available. One such algorithm, AutoGAD, is tested here via two separate robust parameter design techniques to determine optimal parameters for consistent performance on a range of data with large attribute variances. Additionally, the results of the two techniques are compared for overall e ectiveness. The results of the test as well as optimal parameters for AutoGAD are presented and future research e orts proposed.

Parametre knihy

Zaradenie knihy Knihy po anglicky Society & social sciences Education

• Celý názov: Using Multiple Robust Parameter Design Techniques to Improve Hyperspectral Anomaly Detection Algorithm Performance
• Autor: Matthew T Davis
• Jazyk: Angličtina
• Väzba: Brožovaná
• Počet strán: 160
• EAN: 9781288229970
• ISBN: 9781288229970
• ID: 08239730
• Nakladateľ: Biblioscholar
• Hmotnosť: 299 g
• Rozmery: 246 × 189 × 9 mm
• Dátum vydania: 01. October 2012

Obľúbené z iného súdka

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