Internet-scale pattern recognition new techniques for voluminous data sets and data clouds

This cutting-edge reference outlines the underlying theory and principles of efficient and effective distributed pattern recognition involving one-shot learning and in-network processing for different types of applications, including multimedia retrieval systems and event detection over different ne...

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Detalles Bibliográficos
Autor principal: Muhamad Amin, Anang Hudaya (-)
Otros Autores: Khan, Asad, Nasution, Benny
Formato: Libro electrónico
Idioma:Inglés
Publicado: Boca Raton : CRC Press c2013.
Edición:1st edition
Materias:
Ver en Biblioteca Universitat Ramon Llull:https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009628472306719
Descripción
Sumario:This cutting-edge reference outlines the underlying theory and principles of efficient and effective distributed pattern recognition involving one-shot learning and in-network processing for different types of applications, including multimedia retrieval systems and event detection over different network environments. Investigating one-shot learning and in-network processing as complementary mechanisms for efficient and accurate distributed pattern analyses, it presents the technical aspects related to the development of scalable pattern recognition using a number of contemporary application development tools. It also considers scalability of pattern recognition schemes when dealing with such data--
Notas:A Chapman & Hall book.
Descripción Física:1 online resource (196 p.)
Bibliografía:Includes bibliographical references (p. 167-175) and index.
ISBN:9780429096471
9781466510975