| 书目名称 | High-Dimensional and Low-Quality Visual Information Processing | | 副标题 | From Structured Sens | | 编辑 | Yue Deng | | 视频video | | | 概述 | Nominated by Tsinghua University as an outstanding Ph.D. thesis.Proposes a number of computational models to handle the Big Data challenges in visual information processing.Solves a number of real-wor | | 丛书名称 | Springer Theses | | 图书封面 |  | | 描述 | .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.. | | 出版日期 | Book 2015 | | 关键词 | Compressive Sensing; Computer Vision; Discriminative Learning, Information Theory, Optimization; Image | | 版次 | 1 | | doi | https://doi.org/10.1007/978-3-662-44526-6 | | isbn_softcover | 978-3-662-52563-0 | | isbn_ebook | 978-3-662-44526-6Series ISSN 2190-5053 Series E-ISSN 2190-5061 | | issn_series | 2190-5053 | | copyright | Springer-Verlag Berlin Heidelberg 2015 |
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发表于 2025-3-21 17:28:11
