Publikationen
Zeige Ergebnisse 21 - 26 von 26
Laves, M. H., Ihler, S., Ortmaier, T., & Kahrs, L. A. (2019). Quantifying the uncertainty of deep learning-based computer-aided diagnosis for patient safety. Current Directions in Biomedical Engineering, 5(1), 223-226. https://doi.org/10.1515/cdbme-2019-0057
Laves, M.-H., Ihler, S., Kahrs, L. A., & Ortmaier, T. (2019). Retinal OCT disease classification with variational autoencoder regularization. Vorabveröffentlichung online. https://doi.org/10.48550/arXiv.1904.00790
Laves, M. H., Ihler, S., Kahrs, L. A., & Ortmaier, T. (2019). Semantic denoising autoencoders for retinal optical coherence tomography. In European Conference on Biomedical Optics, ECBO_2019 Artikel 11078_43 (Optics InfoBase Conference Papers; Band Part F142-ECBO 2019). OSA - The Optical Society. https://doi.org/10.1117/12.2526936
Laves, M.-H., Ihler, S., & Ortmaier, T. (2019). Uncertainty Quantification in Computer-Aided Diagnosis: Make Your Model say "I don't know" for Ambiguous Cases. Vorabveröffentlichung online. https://doi.org/10.48550/arXiv.1908.00792
Laves, M.-H., Ihler, S., Kortmann, K.-P., & Ortmaier, T. (2019). Well-calibrated Model Uncertainty with Temperature Scaling for Dropout Variational Inference. Vorabveröffentlichung online. https://doi.org/10.48550/arXiv.1909.13550
Modes, V., Ihler, S., Ortmaier, T., Nabavi, A., & Burgner Kahrs, J. (2018). Towards Concentric Tube Robots for Microsurgery: First Results in Eye-to-hand Visual Servoing. In Proceedings of The Hamlyn Symposium on Medical Robotics 2018 (S. 77-78) https://doi.org/10.31256/hsmr2018.39