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High-dimensional and low-quality visual information processing

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  • 99 Seiten
  • 4 Lesestunden

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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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High-dimensional and low-quality visual information processing, Yue Deng

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Erscheinungsdatum
2015
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(Hardcover)
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