97 citations · 101 across the 2 of their papers we have counts for
2 papers
eess.IV2024★ 97 cited
DALSA: Domain Adaptation for Supervised Learning From Sparsely Annotated MR Images
Michael Götz, Christian Weber, Franciszek Binczyk +7
We propose a new method that employs transfer learning techniques to effectively correct sampling selection errors introduced by sparse annotations during supervised learning for a…
eess.IV2024★ 4 cited
Input Data Adaptive Learning (IDAL) for Sub-acute Ischemic Stroke Lesion Segmentation
Michael Götz, Christian Weber, Christoph Kolb +1
In machine learning larger databases are usually associated with higher classification accuracy due to better generalization. This generalization may lead to non-optimal classifier…