大葉大學圖書館 |

High-dimensional and low-quality visual information processing[electronic resource] :from structured sensing and understanding /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
杜威分類號:	006.37
書名/作者:	High-dimensional and low-quality visual information processing : from structured sensing and understanding // by Yue Deng.
作者:	Deng, Yue.
出版者:	Berlin, Heidelberg : : Springer Berlin Heidelberg :, 2015.
面頁冊數:	xv, 99 p. : : ill., digital ;; 24 cm.
Contained By:	Springer eBooks
標題:	Computer vision.
標題:	Image processing.
標題:	Optical data processing.
標題:	Engineering.
標題:	Signal, Image and Speech Processing.
標題:	Image Processing and Computer Vision.
標題:	Data Structures, Cryptology and Information Theory.
標題:	Data Mining and Knowledge Discovery.
ISBN:	9783662445266 (electronic bk.)
ISBN:	9783662445259 (paper)
內容註:	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.
摘要、提要註:	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.
電子資源:	http://dx.doi.org/10.1007/978-3-662-44526-6

High-dimensional and low-quality visual information processing[electronic resource] :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:

403529
Computer vision.

LC Class. No.: TA1634

Dewey Class. No.: 006.37

High-dimensional and low-quality visual information processing[electronic resource] :from structured sensing and understanding /
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