High-Dimensional and Low-Quality Visual Information Processing

From Structured Sensing and Understanding

By: Yue Deng

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Hardcover | 18 September 2014

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Hardcover
116 Pages

Dimensions(cm)
23.5 x 15.49 x 0.79

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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.

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