Frank Schebesch



Joint Super-Resolution and Rectification for Solar Cell Inspection (2021) Hoffmann M, Köhler T, Doll B, Schebesch F, Talkenberg F, Peters IM, Brabec C, et al. Journal article, Original article Learning with Known Operators reduces Maximum Training Error Bounds. (2019) Maier A, Syben-Leisner C, Stimpel B, Würfl T, Hoffmann M, Schebesch F, Fu W, et al. Journal article Detection of Unseen Low-Contrast Signals Using Classic and Novel Model Observers (2019) Xu Y, Schebesch F, Ravikumar N, Maier A Conference contribution Towards an analytic model: Describing the effect of scan angle and slice thickness on the in-plane spatial resolution of calcications in digital breast tomosynthesis (2018) Luckner C, Schebesch F, Mertelmeier T, Fieselmann A, Maier A, Ritschl L Conference contribution, Original article Precision Learning: Towards Use of Known Operators in Neural Networks (2018) Maier A, Schebesch F, Syben-Leisner C, Würfl T, Steidl S, Choi JH, Fahrig R Conference contribution On the Influence of Acquisition Angle and Slice Thickness on the in-plane Spatial Resolution of Calcifications in Digital Breast Tomosynthesis (2018) Luckner C, Schebesch F, Syben-Leisner C, Mertelmeier T, Maier A, Ritschl L Conference contribution A Hybrid Approach for Virtual Clinical Trials for Mammographic Imaging (2018) Schebesch F, Magdalena H, Mertelmeier T, Maier A, Ritschl L Conference contribution UI-Net: Interactive Artificial Neural Networks for Iterative Image Segmentation Based on a User Model (2017) Amrehn M, Gaube S, Unberath M, Schebesch F, Horz T, Strumia M, Steidl S, et al. Conference contribution Breast density assessment using wavelet features on mammograms (2017) Schebesch F, Unberath M, Andersen I, Maier A Conference contribution Lesion Ground Truth Estimation for a Physical Breast Phantom (2017) Hanif S, Schebesch F, Jerebko A, Ritschl L, Mertelmeier T, Maier A Conference contribution