Elenco seminari del ciclo di seminari
“ INTERNATIONAL PH.D. SUMMER SCHOOL MATHEMATICS AND MACHINE LEARNING FOR IMAGE ANALYSIS”

The International Summer School aims to tackle cross-cutting mathematical approaches to imaging sciences and machine/deep learning, essential for young PhD students/researchers interested in discovering the fascinating connections between these disciplines. The school aims at providing the students with both the theoretical and applied foundations of the mathematics of machine learning for imaging with an overview to challenging applications.

analisi numerica

This seminar will cover some concepts and recent advances in the emerging field of self-supervised learning methods for solving imaging inverse problems with deep neural networks. Self-supervised learning is a fundamental tool deploying deep learning solutions in scientific and medical imaging applications where obtaining a large dataset of ground-truth images is very expensive or impossible. The seminar will present different self-supervised methods, discuss their theoretical underpinnings and present practical self-supervised imaging applications. Finally, I will discuss my experience developing and collaborating on open-source software for science (https://deepinv.github.io/), and some of the lessons learned along the way.

Elenco seminari del ciclo di seminari “ INTERNATIONAL PH.D. SUMMER SCHOOL MATHEMATICS AND MACHINE LEARNING FOR IMAGE ANALYSIS”

Elenco seminari del ciclo di seminari
“ INTERNATIONAL PH.D. SUMMER SCHOOL MATHEMATICS AND MACHINE LEARNING FOR IMAGE ANALYSIS”