Physical Models and Machine Learning for Scientific Imaging - Julien Mairal (INRIA, Univ. Grenoble Alpes)

Deep learning has revolutionized image processing and is often considered to outperform classical approaches based on accurate modeling of the image formation process. In this presentation, we will discuss the interplay between model-based and learning-based paradigms, and show that hybrid approaches show great promises for scientific imaging.  We will present two applications on super-resolution and high-dynamic range imaging from photographic bursts, and exoplanet detection from direct high-contrast imaging.

Contact:  Delphine Ropers