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...
Saved in:
| Main Author: | |
|---|---|
| Corporate Author: | |
| Format: | Electronic eBook |
| Language: | English |
| Published: |
Berlin, Heidelberg :
Springer Berlin Heidelberg : Imprint: Springer,
2015.
|
| Edition: | 1st ed. 2015. |
| Series: | Springer Theses, Recognizing Outstanding Ph.D. Research,
|
| Subjects: | |
| Online Access: | https://doi.org/10.1007/978-3-662-44526-6 |
| Tags: |
Add Tag
No Tags, Be the first to tag this 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. |
|---|---|
| Physical Description: | XV, 99 p. 23 illus., 18 illus. in color. online resource. |
| ISBN: | 9783662445266 |
| ISSN: | 2190-5053 |