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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.
| Autorius: | Yue Deng |
| Serija: | Springer Theses |
| Leidėjas: | Springer Berlin Heidelberg |
| Išleidimo metai: | 2014 |
| Knygos puslapių skaičius: | 116 |
| ISBN-10: | 3662445255 |
| ISBN-13: | 9783662445259 |
| Formatas: | 241 x 160 x 13 mm. Knyga kietu viršeliu |
| Kalba: | Anglų |
Parašykite atsiliepimą apie „High-Dimensional and Low-Quality Visual Information Processing: From Structured Sensing and Understanding“
