11 citations · 12 across the 10 of their papers we have counts for
3 papers · 1 filter
On the importance of local and global feature learning for automated measurable residual disease detection in flow cytometry data
Lisa Weijler, Michael Reiter, Pedro Hermosilla +2
This paper evaluates various deep learning methods for measurable residual disease (MRD) detection in flow cytometry (FCM) data, addressing questions regarding the benefits of mode…
TTT-KD: Test-Time Training for 3D Semantic Segmentation through Knowledge Distillation from Foundation Models
Lisa Weijler, Muhammad Jehanzeb Mirza, Leon Sick +2
Test-Time Training (TTT) proposes to adapt a pre-trained network to changing data distributions on-the-fly. In this work, we propose the first TTT method for 3D semantic segmentati…
PPSURF: Combining Patches and Point Convolutions for Detailed Surface Reconstruction
Philipp Erler, Lizeth Fuentes, Pedro Hermosilla +3
3D surface reconstruction from point clouds is a key step in areas such as content creation, archaeology, digital cultural heritage, and engineering. Current approaches either try…