Evaluation of Swin Transformer and knowledge transfer for denoising of super-resolution structured illumination microscopy data
Z.H. Shah, M. Müller, W. Hübner, T.-C. Wang, D. Telman, T. Huser, W. Schenck, GigaScience 13 (2024).

Image restoration in frequency space using complex-valued CNNs
Z.H. Shah, M. Müller, W. Hübner, H. Ortkrass, B. Hammer, T. Huser, W. Schenck, Frontiers in Artificial Intelligence 7 (2024).

Impact of different loss functions on denoising of microscopic images
Z.H. Shah, M. Muller, B. Hammer, T. Huser, W. Schenck, in: 2022 International Joint Conference on Neural Networks (IJCNN), IEEE, 2022, pp. 1–10.

Deep-learning based denoising and reconstruction of super-resolution structured illumination microscopy images
Z.H. Shah, M. Müller, T.-C. Wang, P.M. Scheidig, A. Schneider, M. Schüttpelz, T. Huser, W. Schenck, Photonics Research 9 (2021).

Deep-learning based denoising and reconstruction of super-resolution structured illumination microscopy images
Z.H. Shah, M. Müller, T.-C. Wang, P.M. Scheidig, A. Schneider, M. Schüttpelz, T. Huser, W. Schenck, Deep-Learning Based Denoising and Reconstruction of Super-Resolution Structured Illumination Microscopy Images, Cold Spring Harbor Laboratory, 2020.