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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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Bibliographic Details
Main Author: Deng, Yue
Format: eBook
Language:English
Published: Berlin, Heidelberg Springer Berlin Heidelberg 2015, 2015
Edition:1st ed. 2015
Series:Springer Theses, Recognizing Outstanding Ph.D. Research
Subjects:
Computer Vision
Data Structures And Information Theory
Data Mining
Signal, Speech And Image Processing
Information Theory
Data Structures (computer Science)
Data Mining And Knowledge Discovery
Signal Processing
Online Access:
Collection: Springer eBooks 2005- - Collection details see MPG.ReNa
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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 
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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 

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