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

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Bibliographic Details
Author / Creator:Deng, Yue, author.
Imprint:Heidelberg : Springer, [2015]
©2015
Description:1 online resource.
Language:English
Series:Springer theses
Springer theses.
Subject:
Format: E-Resource Book
URL for this record:http://pi.lib.uchicago.edu/1001/cat/bib/11087604
Hidden Bibliographic Details
ISBN:9783662445266
3662445263
9783662445259
3662445255
Notes:"Doctoral thesis accepted by Tsinghua University, Beijing, China."
Includes bibliographical references and index.
Print version record.
Summary: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.
Other form:Print version: Deng, Yue. High-dimensional and low-quality visual information processing 3662445255
Standard no.:10.1007/978-3-662-44526-6