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High-Dimensional and Low-Quality Visual Information Processing
From Structured Sensing and Understanding
eBook
Sofort lieferbar | Lieferzeit: Sofort lieferbar I
ISBN-13:
9783662445266
Veröffentl:
2014
Einband:
eBook
Seiten:
99
Autor:
Yue Deng
Serie:
Springer Theses
eBook Typ:
PDF
eBook Format:
Reflowable eBook
Kopierschutz:
Digital Watermark [Social-DRM]
Sprache:
Englisch
Beschreibung:
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.
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.
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.