Isbn: 9783659363528 - hyperspectral face recognition: using multidimensional clustering on hyperspectral face images (5 resultados)

- Tapa blanda
Librería: preigu, Osnabrück, Alemaniapreigu
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 199,60
Envío por EUR 70,00Se envía de Alemania a Estados Unidos de AmericaCantidad disponible: 5 disponibles
Taschenbuch. Condición: Neu. Hyperspectral Face Recognition | Using Multidimensional Clustering on Hyperspectral Face Images | Vinayak Bharadi (u. a.) | Taschenbuch | 100 S. | Englisch | 2014 | LAP LAMBERT Academic Publishing | EAN 9783659363528 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. …

- 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 54,90
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 -In this book the hyperspectral face recognition system is explored in the context of digital signal & image processing techniques. Hyperspectral images contain a wealth of data, but interpreting them requires an understanding of exactly what properties of human face we are trying to measure, and how they relate to the measurements actually made by the hyperspectral sensor. With the availability of hyperspectral face data it is possible to build systems on this. Main focus current research is to use hyperspectral face images in order to recognition the face. Hyperspectral face images with 33 band are used for generation of Vector Quantization based feature vector extraction process. These images are grouped into eleven sub-bands of three images each. Algorithms like Kekre's Fast Codebook Generation (KFCG) Algorithm and Kekre's Median Codebook Generation (KMCG) Algorithm are used to generate cod Elektronisches Buch for each sub-band and then store into feature vector database. This feature vector set is used for identification of the person. . K-Nearest Neighborhood classifier (K-NN) is used and performance is evaluated, metrics such as EER, SPI, PI are used for benchmarking. 100 pp. Englisch.…

- Tapa blanda
- Impresión bajo demanda
Librería: moluna, Greven, Alemaniamoluna
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 46,15
Envío por EUR 48,99Se envía de Alemania a Estados Unidos de AmericaCantidad disponible: Más de 20 disponibles
Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Bharadi VinayakDr. V. A. Bharadi has received B.E. Electronics Engg.in 2002 & M. E. Electronics & Telecomm in 2007 fromMumbai University. He has completed Ph.D. inEngineering (Biometrics Authentication Systems)fromNMIMS University i. …

- Tapa blanda
- Impresión bajo demanda
Librería: AHA-BUCH GmbH, Einbeck, AlemaniaAHA-BUCH GmbH
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 54,90
Envío por EUR 60,84Se envía de Alemania a Estados Unidos de AmericaCantidad disponible: 1 disponible
Taschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - In this book the hyperspectral face recognition system is explored in the context of digital signal & image processing techniques. Hyperspectral images contain a wealth of data, but interpreting them requires an understanding of exactly what properties of human face we are trying to measure, and how they relate to the measurements actually made by the hyperspectral sensor. With the availability of hyperspectral face data it is possible to build systems on this. Main focus current research is to use hyperspectral face images in order to recognition the face. Hyperspectral face images with 33 band are used for generation of Vector Quantization based feature vector extraction process. These images are grouped into eleven sub-bands of three images each. Algorithms like Kekre's Fast Codebook Generation (KFCG) Algorithm and Kekre's Median Codebook Generation (KMCG) Algorithm are used to generate cod Elektronisches Buch for each sub-band and then store into feature vector database. This feature vector set is used for identification of the person. . K-Nearest Neighborhood classifier (K-NN) is used and performance is evaluated, metrics such as EER, SPI, PI are used for benchmarking.…

- Tapa blanda
- Impresión bajo demanda
Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemaniabuchversandmimpf2000
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 199,60
Envío por EUR 60,00Se envía de Alemania a Estados Unidos de AmericaCantidad disponible: 1 disponible
Taschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -In this book the hyperspectral face recognition system is explored in the context of digital signal & image processing techniques. Hyperspectral images contain a wealth of data, but interpreting them requires an understanding of exactly what properties of human face we are trying to measure, and how they relate to the measurements actually made by the hyperspectral sensor. With the availability of hyperspectral face data it is possible to build systems on this. Main focus current research is to use hyperspectral face images in order to recognition the face. Hyperspectral face images with 33 band are used for generation of Vector Quantization based feature vector extraction process. These images are grouped into eleven sub-bands of three images each. Algorithms like Kekre's Fast Codebook Generation (KFCG) Algorithm and Kekre's Median Codebook Generation (KMCG) Algorithm are used to generate cod Elektronisches Buch for each sub-band and then store into feature vector database. This feature vector set is used for identification of the person. . K-Nearest Neighborhood classifier (K-NN) is used and performance is evaluated, metrics such as EER, SPI, PI are used for benchmarking.OmniScriptum SRL, Str. Armeneasca 28/1, office 1, 2012 Chisinau 100 pp. Englisch.…