Librería: Ria Christie Collections, Uxbridge, Reino Unido
EUR 163,11
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Librería: GreatBookPricesUK, Woodford Green, Reino Unido
EUR 163,10
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Librería: GreatBookPrices, Columbia, MD, Estados Unidos de America
EUR 179,87
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Librería: GreatBookPrices, Columbia, MD, Estados Unidos de America
EUR 181,19
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Añadir al carritoCondición: As New. Unread book in perfect condition.
Librería: GreatBookPricesUK, Woodford Green, Reino Unido
EUR 181,64
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Añadir al carritoCondición: As New. Unread book in perfect condition.
Librería: Books Puddle, New York, NY, Estados Unidos de America
EUR 210,21
Cantidad disponible: 4 disponibles
Añadir al carritoCondición: New. pp. 296.
Idioma: Inglés
Publicado por Kluwer Academic Publishers, 1994
ISBN 10: 0792394917 ISBN 13: 9780792394914
Librería: Kennys Bookshop and Art Galleries Ltd., Galway, GY, Irlanda
EUR 201,45
Cantidad disponible: 15 disponibles
Añadir al carritoCondición: New. Presents the closed-loop image segmentation system that incorporates genetic and other algorithms to adapt the segmentation process to changes in image characteristics caused by variable environmental conditions, such as time of day, time of year and weather. Series: The Springer International Series in Engineering and Computer Science. Num Pages: 271 pages, biography. BIC Classification: UYQV. Category: (P) Professional & Vocational; (UP) Postgraduate, Research & Scholarly. Dimension: 235 x 155 x 17. Weight in Grams: 1310. . 1994. Hardback. . . . .
EUR 180,46
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Añadir al carritoGebunden. Condición: New. Image segmentation is generally the first task in any automated image understanding application, such as autonomous vehicle navigation, object recognition, photointerpretation, etc. All subsequent tasks, such as feature extraction, object detection, and .
Idioma: Inglés
Publicado por Kluwer Academic Publishers, 1994
ISBN 10: 0792394917 ISBN 13: 9780792394914
Librería: Kennys Bookstore, Olney, MD, Estados Unidos de America
EUR 251,26
Cantidad disponible: 15 disponibles
Añadir al carritoCondición: New. Presents the closed-loop image segmentation system that incorporates genetic and other algorithms to adapt the segmentation process to changes in image characteristics caused by variable environmental conditions, such as time of day, time of year and weather. Series: The Springer International Series in Engineering and Computer Science. Num Pages: 271 pages, biography. BIC Classification: UYQV. Category: (P) Professional & Vocational; (UP) Postgraduate, Research & Scholarly. Dimension: 235 x 155 x 17. Weight in Grams: 1310. . 1994. Hardback. . . . . Books ship from the US and Ireland.
EUR 247,94
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Añadir al carritoBuch. Condición: Neu. Neuware - Image segmentation is generally the first task in any automated image understanding application, such as autonomous vehicle navigation, object recognition, photointerpretation, etc. All subsequent tasks, such as feature extraction, object detection, and object recognition, rely heavily on the quality of segmentation. One of the fundamental weaknesses of current image segmentation algorithms is their inability to adapt the segmentation process as real-world changes are reflected in the image. Only after numerous modifications to an algorithm's control parameters can any current image segmentation technique be used to handle the diversity of images encountered in real-world applications. Genetic Learning for Adaptive Image Segmentation presents the first closed-loop image segmentation system that incorporates genetic and other algorithms to adapt the segmentation process to changes in image characteristics caused by variable environmental conditions, such as time of day, time of year, weather, etc. Image segmentation performance is evaluated using multiple measures of segmentation quality. These quality measures include global characteristics of the entire image as well as local features of individual object regions in the image. This adaptive image segmentation system provides continuous adaptation to normal environmental variations, exhibits learning capabilities, and provides robust performance when interacting with a dynamic environment. This research is directed towards adapting the performance of a well known existing segmentation algorithm (Phoenix) across a wide variety of environmental conditions which cause changes in the image characteristics. The book presents a large number of experimental results and compares performance with standard techniques used in computer vision for both consistency and quality of segmentation results. These results demonstrate, (a) the ability to adapt the segmentation performance in both indoor and outdoor color imagery, and (b) that learning from experience can be used to improve the segmentation performance over time.
Librería: Majestic Books, Hounslow, Reino Unido
EUR 219,62
Cantidad disponible: 4 disponibles
Añadir al carritoCondición: New. Print on Demand pp. 296 52:B&W 6.14 x 9.21in or 234 x 156mm (Royal 8vo) Case Laminate on White w/Gloss Lam.
Librería: Biblios, Frankfurt am main, HESSE, Alemania
EUR 220,97
Cantidad disponible: 4 disponibles
Añadir al carritoCondición: New. PRINT ON DEMAND pp. 296.