書目名稱 | Handbook of Mathematical Models and Algorithms in Computer Vision and Imaging | 副標題 | Mathematical Imaging | 編輯 | Ke Chen,Carola-Bibiane Sch?nlieb,Laurent Younes | 視頻video | http://file.papertrans.cn/422/421624/421624.mp4 | 概述 | Provides ready access to state-of-the-art topics in imaging and visio.Connects pure and applied analysis through geometry.Written by leading researchers in imaging and vision | 圖書封面 |  | 描述 | .This handbook gathers together the state of the art on?mathematical models?and algorithms for imaging and vision. Its emphasis lies on?rigorous mathematical?methods, which represent the optimal solutions to a class of imaging and vision problems, and on effective algorithms, which are necessary for the methods to be translated to practical use in various applications. Viewing discrete images as data sampled from functional surfaces enables the use of advanced tools from calculus, functions and calculus of variations, and?nonlinear?optimization, and provides the basis of high-resolution imaging through?geometry and?variational models. Besides,?optimization naturally connects traditional model-driven approaches to the emerging data-driven approaches of machine and deep learning.??No other framework can provide comparable accuracy and precision to imaging and vision...Written by leading researchers in imaging and?vision, the chapters in this handbook all start with gentle introductions, which make this work accessible to graduate students. For newcomers to the field, the book provides a comprehensive and fast-track introduction to the content, to save time and get on with tackling ne | 出版日期 | Reference work 2023 | 關鍵詞 | Mathematical Imaging and Vision; Nonlinear optimization; Calculus of variation; Efficient algorithms; De | 版次 | 1 | doi | https://doi.org/10.1007/978-3-030-98661-2 | isbn_ebook | 978-3-030-98661-2 | copyright | Springer Nature Switzerland AG 2023 |
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