Deep Semi Supervised Generative Learning for Automated PD-L1 Tumor Cell Scoring on NSCLC Tissue Needle Biopsies. - Ansh Kapil; Armin Meier; Aleksandra Zuraw; Keith Steele; Marlon Rebelatto; Günter Schmidt 001; Nicolas Brieu (CoRR, 2018)

Learning without prejudice: Avoiding bias in webly-supervised action recognition. - Christian Rupprecht 001; Ansh Kapil; Nan Liu; Lamberto Ballan; Federico Tombari (Comput. Vis. Image Underst., 2018)

DASGAN - Joint Domain Adaptation and Segmentation for the Analysis of Epithelial Regions in Histopathology PD-L1 Images. - Ansh Kapil; Tobias Wiestler; Simon Lanzmich; Abraham Silva; Keith Steele; Marlon Rebelatto; Günter Schmidt 001; Nicolas Brieu (CoRR, 2019)

Domain Adaptation-based Augmentation for Weakly Supervised Nuclei Detection. - Nicolas Brieu; Armin Meier; Ansh Kapil; Ralf Schönmeyer; Christos G. Gavriel; Peter D. Caie; Günter Schmidt 001 (CoRR, 2019)

Domain Adaptation-Based Deep Learning for Automated Tumor Cell (TC) Scoring and Survival Analysis on PD-L1 Stained Tissue Images. - Ansh Kapil; Armin Meier; Keith Steele; Marlon Rebelatto; Katharina Nekolla; Alexander Haragan; Abraham Silva; Aleksandra Zuraw; Craig Barker; Marietta L. Scott; Tobias Wiestler; Simon Lanzmich; et al. (IEEE Trans. Medical Imaging, 2021)

Stain Isolation-based Guidance for Improved Stain Translation. - Nicolas Brieu; Felix J. Segerer; Ansh Kapil; Philipp Wortmann; Günter Schmidt 001 (CoRR, 2022)

Novel Deep Learning Approach to Derive Cytokeratin Expression and Epithelium Segmentation from DAPI. - Felix Jakob Segerer; Katharina Nekolla; Lorenz Rognoni; Ansh Kapil; Markus Schick; Helen Angell; Günter Schmidt 001 (CoRR, 2022)