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High-Dimensional and Low-Quality Visual Information Processing

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High-Dimensional and Low-Quality Visual Information Processing Synopsis

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.

About This Edition

ISBN: 9783662445259
Publication date:
Author: Yue Deng
Publisher: Springer an imprint of Springer Berlin Heidelberg
Format: Hardback
Pagination: 99 pages
Series: Springer Theses
Genres: Electronics engineering
Expert systems / knowledge-based systems
Computer vision
Digital signal processing (DSP)
Algorithms and data structures
Data mining
Information theory