ENGinnSAND: A Reference Dataset for Monocular Depth Prediction of Line Structures - Hubert Bottesch; Christoph Angermann; Christian Laubichler; Constantin Kiesling; Markus Haltmeier (Machine Learning, Optimization, and Data Science - 10th International Conference, LOD 2024, Castiglione della Pescaia, Italy, September 22-25, 2024, Revised Selected Papers, Part II, 2024)

Surface topography characterization using a simple optical device and artificial neural networks - Christoph Angermann; Markus Haltmeier; Christian Laubichler; Steinbjörn Jónsson; Matthias Schwab; Adéla Moravová; Constantin Kiesling; Martin Kober; Wolfgang Fimml (Eng. Appl. Artif. Intell., 2023)

Unsupervised single-shot depth estimation using perceptual reconstruction - Christoph Angermann; Matthias Schwab; Markus Haltmeier; Christian Laubichler; Steinbjörn Jónsson (Mach. Vis. Appl., 2023)

Correction: Unsupervised single-shot depth estimation using perceptual reconstruction - Christoph Angermann; Matthias Schwab; Markus Haltmeier; Christian Laubichler; Steinbjörn Jónsson (Mach. Vis. Appl., 2023)

Uncertainty-Aware Null Space Networks for Data-Consistent Image Reconstruction - Christoph Angermann; Simon Göppel; Markus Haltmeier (CoRR, 2023)

Three-dimensional Bone Image Synthesis with Generative Adversarial Networks - Christoph Angermann; Johannes Bereiter-Payr; Kerstin Stock; Markus Haltmeier; Gerald Degenhart (CoRR, 2023)

Unsupervised Joint Image Transfer and Uncertainty Quantification Using Patch Invariant Networks - Christoph Angermann; Markus Haltmeier; Ahsan Raza Siyal (Computer Vision - ECCV 2022 Workshops - Tel Aviv, Israel, October 23-27, 2022, Proceedings, Part VIII, 2022)

Unsupervised Single-shot Depth Estimation using Perceptual Reconstruction - Christoph Angermann; Matthias Schwab; Markus Haltmeier; Christian Laubichler; Steinbjörn Jónsson (CoRR, 2022)

Unsupervised Joint Image Transfer and Uncertainty Quantification using Patch Invariant Networks - Christoph Angermann; Markus Haltmeier; Ahsan Raza Siyal (CoRR, 2022)

Deep structure learning using feature extraction in trained projection space - Christoph Angermann; Markus Haltmeier (Comput. Electr. Eng., 2021)

Machine Learning for Nondestructive Wear Assessment in Large Internal Combustion Engines - Christoph Angermann; Steinbjörn Jónsson; Markus Haltmeier; Adéla Moravová; Christian Laubichler; Constantin Kiesling; Martin Kober; Wolfgang Fimml (CoRR, 2021)

PiNet: Deep Structure Learning using Feature Extraction in Trained Projection Space - Christoph Angermann; Markus Haltmeier (CoRR, 2020)

Random 2.5D U-net for Fully 3D Segmentation - Christoph Angermann; Markus Haltmeier (Machine Learning and Medical Engineering for Cardiovascular Health and Intravascular Imaging and Computer Assisted Stenting - First International Workshop, MLMECH 2019, and 8th Joint International Workshop, CVII-STENT 2019, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 13, 2019, Proceedings, 2019)

Projection-Based 2.5D U-net Architecture for Fast Volumetric Segmentation - Christoph Angermann; Markus Haltmeier; Ruth Steiger; Sergiy Pereverzyev Jr.; Elke Ruth Gizewski (CoRR, 2019)

Random 2.5D U-net for Fully 3D Segmentation - Christoph Angermann; Markus Haltmeier (CoRR, 2019)