Contacto
Cómo comprar
Entrega
Guía de compras
Using Multiple Robust Parameter Design Techniques to Improve Hyperspectral Anomaly Detection Algorithm Performance
Inglés
143 b
Política de devolución de 30 días
Clientes que también han comprado
/
Tapa blanda
27.69
€
/
Tapa dura
7.39
€
/
Adobe ePub DRM
73.89
€
/
Tapa blanda
47.29
€
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.
Sobre el libro
Inglés
Categorías
Regale este libro hoy
Es fácil
1 Añadir al carrito y elegir Entregar como regalo en el checkout 2 Le enviaremos un vale 3 El libro llegará a la dirección del destinatarioTambién puede interesarle
/
Tapa dura
18.89
€
/
Tapa blanda
6.99
€
/
Tapa blanda
29.89
€