3 papers
cs.CV2026
Foundation Models vs. Radiomics for Lung Computed Tomography: A Benchmark of Feature Extractors, Classification Heads, and Segmentation Choices
Nils Neukirch, Martin Maurer, Nils Strodthoff
Radiomics is the established approach for CT-based lung cancer phenotyping, yet comparisons with foundation models rarely isolate contributions of feature extractor, classification…
cs.LG2026
FeatMap: Understanding image manipulation in the feature space and its implications for feature space geometry
Elias B. Krey, Nils Neukirch, Nils Strodthoff
Intermediate feature representations represent the backbone for the expressivity and adaptability of deep neural networks. However, their geometric structure remains poorly underst…
cs.CV2026
FeatInv: Spatially resolved mapping from feature space to input space using conditional diffusion models
Nils Neukirch, Johanna Vielhaben, Nils Strodthoff
Internal representations are crucial for understanding deep neural networks, such as their properties and reasoning patterns, but remain difficult to interpret. While mapping from…