**Przedmiot prowadzony przez dr. Artura Yakimovicha z The Center for Advanced Systems Understanding (CASUS). Prezedmiot prowadzony jest nieregularnie:
Deep learning is rapidly revolutionising biomedical image image analysis. Yet, unlike fields where deep learning is applied to intuitively understandable data domains like photographs, biomedical images are often acquired under domain-specific assumptions using complex equipment to solve tasks with high equivocation. Specialised deep learning algorithms take these priors into account making such scientific papers hard to understand for a computer scientist lacking the necessary background. In this seminar series, we will explore the most recent scientific literature involving deep learning algorithms used in biomedical image analysis. In a group effort, we will understand the priors and assumptions of biomedical image acquisition and analysis and understand the cutting-edge approaches.
Contribution: regular paper reading by all, rotating presentation by individuals or small groups of students.
Start: 13th October 2023 1:30 PM, 2 academic hours (90 min)
Periodicity: Every 2 weeks
Exact Dates: October: 13, 27; November 10, 24; December 8, 22; January 5, 19;
