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...
| Κύριος συγγραφέας: | |
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| Συγγραφή απο Οργανισμό/Αρχή: | |
| Μορφή: | Ηλεκτρονική πηγή Ηλ. βιβλίο |
| Γλώσσα: | English |
| Έκδοση: |
Berlin, Heidelberg :
Springer Berlin Heidelberg : Imprint: Springer,
2015.
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| Σειρά: | Springer Theses, Recognizing Outstanding Ph.D. Research,
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| Θέματα: | |
| Διαθέσιμο Online: | Full Text via HEAL-Link |
| Περίληψη: | 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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| Φυσική περιγραφή: | XV, 99 p. 23 illus., 18 illus. in color. online resource. |
| ISBN: | 9783662445266 |
| ISSN: | 2190-5053 |