• Self-supervised domain adaptation for historical documents using deep learning (CNNs) (Master)

... and more! Check out our research topics and research projects!

• Salim Hermidas - Reimplementation and Extension of DivaServices
• Alain Schaller - Sterile-Zone Perturbations Recognition
• Mattia Pedrazzi - Establishing a CNN baseline for a pT1 (and potentially stage II) CRC cohort dataset
• Atefeh Fakhari - Applying The TEA-Graph Based Analysis to Colorectal Cancer Data

• Pierre Masserey - Generation of Synthetic Documents

Bachelor:

• Gwenael Gendre - Graph-Based Keyword Spotting in Ancient Greek Papyri
• Fabrice Prince - Deep Learning Approach for Epithelium Segmentation in Cancer Image Analysis
• Pablo Wey - Graph Matching for Ground Truthing Chu Nom Characters
• Peguy Njoyim Tchoubith - Machine learning experiments in document image analysis
• Yannis Laaroussi - Data processing and graph visualisation of tumour and T-cell detections
• Max Haller - Ground truth refinement for DIVAHisDB

Master:

• Carl Balmer - Tackling the Hanabi Challenge: Reinforcement Learning for a Cooperative Card Game
• Joel Niklaus - Building a Super-Human Artificial Intelligence for the Swiss Card Game Jass
• Dominic Kohler - Popularity Prediction of Reddit Posts
• Jannis Wallau - Classification of Intestinal Glands using Graph Neural Networks
• Sven Wallau - Transfer Learning for Intestinal Gland Segmentation
• Manuel Drazyk - OCR Constrained Historical Document Synthesis with GANs
• Matteo Badarocco - A POS Tagger Comparison between Prose Text and Poetry
• Marion Schöneweid - Graph representations for H&E Whole Slide Images of Colorectal Cancer
• Jonas Diesbach - Synthetization of Nom characters
• Tanja Küry - Preserving Biodiversity in the Chinko Natural Reserve
• Gwenael Gendre - Character Spotting in Ancient Greek Papyrus