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High-dimensional and low-quality vis...

Deng, Yue.

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High-dimensional and low-quality visual information processing = from structured sensing and understanding /

Record Type:	Electronic resources : Monograph/item
Title/Author:	High-dimensional and low-quality visual information processing/ by Yue Deng.
Reminder of title:	from structured sensing and understanding /
Author:	Deng, Yue.
Published:	Berlin, Heidelberg :Springer Berlin Heidelberg : : 2015.,
Description:	xv, 99 p. :ill., digital ;24 cm.
[NT 15003449]:	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.
Contained By:	Springer eBooks
Subject:	Computer vision. -
Online resource:	http://dx.doi.org/10.1007/978-3-662-44526-6
ISBN:	9783662445266 (electronic bk.)

High-dimensional and low-quality visual information processing = from structured sensing and understanding /
Deng, Yue.

High-dimensional and low-quality visual information processingfrom structured sensing and understanding /[electronic resource] :by Yue Deng. - Berlin, Heidelberg :Springer Berlin Heidelberg :2015. - xv, 99 p. :ill., digital ;24 cm. - Springer theses,2190-5053. - Springer theses..

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.

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.

ISBN: 9783662445266 (electronic bk.)

Standard No.: 10.1007/978-3-662-44526-6doiSubjects--Topical Terms:

540671
Computer vision.

LC Class. No.: TA1634

Dewey Class. No.: 006.37

High-dimensional and low-quality visual information processing = from structured sensing and understanding /
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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.
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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