Special Issue on the Mathematical Foundations of Deep Learning in Imaging Science
Special Issue on the Mathematical Foundations of Deep Learning in Imaging Science
复制标题
影像科学深度学习的数学基础特刊
DOI：
10.1007/s10851-020-00955-8
复制
发表时间：
2020
影响因子：
2
通讯作者：
Vidal, René
中科院分区：
文献类型：
--
作者：
Bruna, Joan;Haber, Eldad;Kutyniok, Gitta;Pock, Thomas;Vidal, René
深度学习方法已经成为最近成像和视觉方法中无所不在且非常成功的一部分。然而，在大多数情况下，它们是在纯粹的经验基础上使用的，而没有对其行为的真实的理解。从科学的角度来看，这是不令人满意的。许多有数学倾向的研究人员都强烈希望了解这些方法成功的理论原因，并找到深度学习和成像科学中数学上成熟的技术之间的关系。这期特刊的目的是展示他们的最新研究成果，并推动这一方向的未来研究。它有12篇文章。为了避免任何利益冲突，其中一位客座编辑作为合著者参与的文章由另一位客座编辑处理。
Deep learning methods have become an omnipresent and highly successful part of recent approaches in imaging and vision. However, in most cases they are used on a purely empirical basis without real understanding of their behavior. From a scientific viewpoint, this is unsatisfying. Many mathematically inclined researchers have a strong desire to understand the theoretical reasons for the success of these approaches and to find relations between deep learning and mathematically well-established techniques in imaging science. The goal of this special issue is to showcase their latest research results and to promote future research in this direction. It features twelve articles. To avoid any conflicts of interest, articles in which one of the guest editors is involved as co-author, have been handled by another guest editor.