9783838324364 - variants of self-organizing maps: applications in image quantization and compression de wang, chao-huang (9 resultados)
- Tapa blanda
Librería: Books Puddle, New York, NY, Estados Unidos de AmericaBooks Puddle
Contactar con el vendedorVendedor de 4 estrellasCondición: Nuevo
EUR 78,02
Envío por EUR 3,48Se envía dentro de Estados Unidos de AmericaCantidad disponible: 4 disponibles
Condición: New.
- Tapa blanda
Librería: preigu, Osnabrück, Alemaniapreigu
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 43,35
Envío por EUR 70,00Se envía de Alemania a Estados Unidos de AmericaCantidad disponible: 5 disponibles
Taschenbuch. Condición: Neu. Variants of Self-Organizing Maps | Applications in Image Quantization and Compression | Chao-Huang Wang (u. a.) | Taschenbuch | 80 S. | Englisch | 2010 | LAP LAMBERT Academic Publishing | EAN 9783838324364 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnab…rück, mail[at]preigu[dot]de | Anbieter: preigu.
- Tapa blanda
Librería: Revaluation Books, Exeter, Reino UnidoRevaluation Books
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 113,49
Envío por EUR 11,80Se envía de Reino Unido a Estados Unidos de AmericaCantidad disponible: 1 disponibles
Paperback. Condición: Brand New. 80 pages. 8.66x5.91x0.19 inches. In Stock.
- Tapa blanda
Librería: Mispah books, Redhill, SURRE, Reino UnidoMispah books
Contactar con el vendedorVendedor de 4 estrellasCondición: Nuevo
EUR 193,32
Envío por EUR 29,51Se envía de Reino Unido a Estados Unidos de AmericaCantidad disponible: 1 disponibles
paperback. Condición: New. NEW. SHIPS FROM MULTIPLE LOCATIONS. book.
- Tapa blanda
- Impresión bajo demanda
Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, AlemaniaBuchWeltWeit Ludwig Meier e.K.
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 49,00
Envío por EUR 23,00Se envía de Alemania a Estados Unidos de AmericaCantidad disponible: 2 disponibles
Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The self-organizing map (SOM) is an unsupervised learning algorithm which has been successfully applied to various applications. In the last several decades, there have been variants of SOM used in many application domains. In this…work, two new SOM algorithms are developed for image quantization and compression. The first algorithm is a sample-size adaptive SOM algorithm that can be used for color quantization of images to adapt to the variations of network parameters and training sample size. Based on the sample-size adaptive self-organizing map, we use the sampling ratio of training data, rather than the conventional weight change between adjacent sweeps, as a stop criterion. As a result, it can significantly speed up the learning process. The second algorithm is a novel classified SOM method for edge preserving quantization of images using an adaptive subcodebook and weighted learning rate. The subcodebook sizes of two classes are automatically adjusted in training iterations that can be estimated incrementally. The proposed weighted learning rate updates the neuron efficiently no matter how large the weighting factor is. 80 pp. Englisch.
- Tapa blanda
- Impresión bajo demanda
Librería: Majestic Books, Hounslow, Reino UnidoMajestic Books
Contactar con el vendedorVendedor de 4 estrellasCondición: Nuevo
EUR 78,04
Envío por EUR 7,67Se envía de Reino Unido a Estados Unidos de AmericaCantidad disponible: 4 disponibles
Condición: New. Print on Demand.
- Tapa blanda
- Impresión bajo demanda
Librería: Biblios, frankfurt am main, HESSE, AlemaniaBiblios
Contactar con el vendedorVendedor de 4 estrellasCondición: Nuevo
EUR 79,63
Envío por EUR 9,95Se envía de Alemania a Estados Unidos de AmericaCantidad disponible: 4 disponibles
Condición: New. PRINT ON DEMAND.
- Tapa blanda
- Impresión bajo demanda
Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemaniabuchversandmimpf2000
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 49,00
Envío por EUR 60,00Se envía de Alemania a Estados Unidos de AmericaCantidad disponible: 1 disponibles
Taschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -The self-organizing map (SOM) is an unsupervised learning algorithm which has been successfully applied to various applications. In the last several decades, there have been variants of SOM used in many application domains. In this work…, two new SOM algorithms are developed for image quantization and compression. The first algorithm is a sample-size adaptive SOM algorithm that can be used for color quantization of images to adapt to the variations of network parameters and training sample size. Based on the sample-size adaptive self-organizing map, we use the sampling ratio of training data, rather than the conventional weight change between adjacent sweeps, as a stop criterion. As a result, it can significantly speed up the learning process. The second algorithm is a novel classified SOM method for edge preserving quantization of images using an adaptive subcodebook and weighted learning rate. The subcodebook sizes of two classes are automatically adjusted in training iterations that can be estimated incrementally. The proposed weighted learning rate updates the neuron efficiently no matter how large the weighting factor is.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 80 pp. Englisch.
- Tapa blanda
- Impresión bajo demanda
Librería: AHA-BUCH GmbH, Einbeck, AlemaniaAHA-BUCH GmbH
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 49,00
Envío por EUR 60,69Se envía de Alemania a Estados Unidos de AmericaCantidad disponible: 1 disponibles
Taschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - The self-organizing map (SOM) is an unsupervised learning algorithm which has been successfully applied to various applications. In the last several decades, there have been variants of SOM used in many application domains. In this work,… two new SOM algorithms are developed for image quantization and compression. The first algorithm is a sample-size adaptive SOM algorithm that can be used for color quantization of images to adapt to the variations of network parameters and training sample size. Based on the sample-size adaptive self-organizing map, we use the sampling ratio of training data, rather than the conventional weight change between adjacent sweeps, as a stop criterion. As a result, it can significantly speed up the learning process. The second algorithm is a novel classified SOM method for edge preserving quantization of images using an adaptive subcodebook and weighted learning rate. The subcodebook sizes of two classes are automatically adjusted in training iterations that can be estimated incrementally. The proposed weighted learning rate updates the neuron efficiently no matter how large the weighting factor is.
