Image classification: A (new) statistical viewpoint

Sophie Langer (TU Darmstadt)

Jun 02. 2022, 15:15 — 16:00

In this talk we consider supervised binary image classification. We introduce a (idealized) statistical model based on grayscale images where each image is subject to some random scaling and random dilation. We discuss different approaches to solve our classification problem. Interestingly, all classifiers improve with increasing dimension $d$ and are able to perfectly separate classes. Our new perspective on an image classification problem helps us not to be affected by the curse of dimensionality.  

Further Information
Venue:
ESI Boltzmann Lecture Hall
Recordings:
Recording
Associated Event:
Computational Uncertainty Quantification: Mathematical Foundations, Methodology & Data (Thematic Programme)
Organizer(s):
Clemens Heitzinger (TU Vienna)
Fabio Nobile (EPFL Lausanne)
Robert Scheichl (U Heidelberg)
Christoph Schwab (ETH Zürich)
Sara van de Geer (ETH Zürich)
Karen Willcox (U of Texas, Austin)