Algebraic topology
Algebraic topology
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DOI：
10.1090/mbk/109/07
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发表时间：
2020-10
期刊：
影响因子：
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通讯作者：
Stefan Friedl
中科院分区：
文献类型：
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作者：
Stefan Friedl
这堂课涵盖了数据分析和图像处理中标准任务的几种基本方法。非排他性和非穷尽性的方法列表：直方图、降维、聚类、fi变换、频率分析、形态方法。。。我们将发展作为这些方法基础的数学理论，这是彻底理解和正确执行方法的基础。此外，我们还将讨论这些方法的实际实现，并将其应用于解决图像去噪、图像去模糊或音乐识别fi等问题。本讲座将使您能够更深入地研究图像和数据分析，并为您跟踪fi领域的最新发展做好准备。如果您想了解使用JPEG进行图像压缩或使用Shazam等工具识别音乐的内部工作原理，请来听这堂课！
This lecture covers several basic methods for standard tasks in data analysis and image processing. A non-exclusive and non-exhaustive list of meth-ods: histograms, dimension reduction, clustering, filters, frequency analysis, morphological methods. . . We will develop the mathematical theory that underlies these methods which is the basis for thorough understanding and proper execution of the method. Moreover, we will deal with the practical implementation of the methods and apply them to solve problems such as image denoising, image deblurring, or music identification. This lecture should enable you to take a deeper dive into image and data analysis and prepares you to follow recent developments in the field. If you want to understand the inner working of image compression with JPEG or music recognition with tools like Shazam, come to this lecture!