High-Dimensional and Low-Quality Visual Information Processing From Structured Sensing and Understanding /

This thesis primarily focuses on how to carry out intelligent sensing and understand the high-dimensional and low-quality visual information. After exploring the inherent structures of the visual data, it proposes a number of computational models covering an extensive range of mathematical topics, i...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Deng, Yue (Autor)
Autor Corporativo: SpringerLink (Online service)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2015.
Edición:1st ed. 2015.
Colección:Springer Theses, Recognizing Outstanding Ph.D. Research,
Temas:
Signal processing.
Computer vision.
Data structures (Computer science).
Information theory.
Data mining.
Signal, Speech and Image Processing .
Computer Vision.
Data Structures and Information Theory.
Data Mining and Knowledge Discovery.
Acceso en línea:Texto Completo

MARC

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100 1 |a Deng, Yue.  |e author.  |4 aut  |4 http://id.loc.gov/vocabulary/relators/aut 
245 1 0 |a High-Dimensional and Low-Quality Visual Information Processing  |h [electronic resource] :  |b From Structured Sensing and Understanding /  |c by Yue Deng. 
250 |a 1st ed. 2015. 
264 1 |a Berlin, Heidelberg :  |b Springer Berlin Heidelberg :  |b Imprint: Springer,  |c 2015. 
300 |a XV, 99 p. 23 illus., 18 illus. in color.  |b online resource. 
336 |a text  |b txt  |2 rdacontent 
337 |a computer  |b c  |2 rdamedia 
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490 1 |a Springer Theses, Recognizing Outstanding Ph.D. Research,  |x 2190-5061 
505 0 |a Introduction -- Sparse Structure for Visual Signal Sensing -- Graph Structure for Visual Signal Sensing -- Discriminative Structure for Visual Signal Understanding -- Information Theoretic Structure for Visual Signal Understanding -- Conclusions. 
520 |a This thesis primarily focuses on how to carry out intelligent sensing and understand the high-dimensional and low-quality visual information. After exploring the inherent structures of the visual data, it proposes a number of computational models covering an extensive range of mathematical topics, including compressive sensing, graph theory, probabilistic learning and information theory. These computational models are also applied to address a number of real-world problems including biometric recognition, stereo signal reconstruction, natural scene parsing, and SAR image processing. 
650 0 |a Signal processing. 
650 0 |a Computer vision. 
650 0 |a Data structures (Computer science). 
650 0 |a Information theory. 
650 0 |a Data mining. 
650 1 4 |a Signal, Speech and Image Processing . 
650 2 4 |a Computer Vision. 
650 2 4 |a Data Structures and Information Theory. 
650 2 4 |a Data Mining and Knowledge Discovery. 
710 2 |a SpringerLink (Online service) 
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776 0 8 |i Printed edition:  |z 9783662445273 
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830 0 |a Springer Theses, Recognizing Outstanding Ph.D. Research,  |x 2190-5061 
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950 |a Engineering (SpringerNature-11647) 
950 |a Engineering (R0) (SpringerNature-43712) 

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