In her work, Ellena Spieß investigates whether large, general-purpose machine learning models offer advantages over smaller, specialized models when sufficient training data are available. She presented the first results of her study, “Impact of Transfer Learning and Model Capacity on Patch-Level Metastasis Detection Across Training Data Regimes.”
Maleen Rettenberger was awarded the Friedrich Wingert Scholarship for her project on improving the generalizability of cell segmentation models without additional training. As part of the Friedrich Wingert Foundation session, she presented the current status of her project. The project is jointly supervised in collaboration with Aalen University.
The conference provided a valuable opportunity to present current research from our institute to an interdisciplinary audience and to exchange ideas with fellow researchers. We are delighted with their successful participation and warmly congratulate both on this achievement.
