Precision Learning
Precision Learning is a research direction, seeking
to integrate known operators into machine learning models to improve
generalization und efficiency.
to integrate known operators into machine learning models to improve
generalization und efficiency.
Known operators have been shown to hold the
potential of reducing maximal error bounds when incorporated into deep
neural networks. This suggests their inclusion could allow models to
learn from less data and increase robustness.
Projects
Participating Scientists
Publications
- Huang Y., Taubmann O., Huang X., Haase V., Lauritsch G., Maier A.:
A New Scale Space Total Variation Algorithm for Limited Angle Tomography
CT-Meeting 2016 (Bamberg, Germany, April 13, 2016 - April 16, 2016)
In: Marc Kachelrieß (ed.): CT-Meeting 2016 Proceedings (The 4th International Meeting on Image Formation in X-Ray Computed Tomography) 2016
URL: https://www5.informatik.uni-erlangen.de/Forschung/Publikationen/2016/Huang16-ANS.pdf
BibTeX: Download - Huang X., Xia Y., Huang Y., Hornegger J., Maier A.:
Overexposure Correction by Mixed One-bit Compressive Sensing for C-Arm CT
Bildverarbeitung für die Medizin 2017 (Heidelberg, March 12, 2017 - March 14, 2017)
In: Klaus Hermann Maier-Hein, geb. Fritzsche, Thomas Martin Deserno, geb. Lehmann, Heinz Handels,Thomas Tolxdorff (ed.): Bildverarbeitung für die Medizin: Algorithmen-Systeme-Anwendungen, Berlin: 2017
DOI: 10.1007/978-3-662-54345-0
URL: https://www5.informatik.uni-erlangen.de/Forschung/Publikationen/2017/Huang17-OCB.pdf
BibTeX: Download - Huang Y., Gao L., Preuhs A., Maier A.:
Field of View Extension in Computed Tomography Using Deep Learning Prior
Bildverarbeitung für die Medizin (Berlin, March 15, 2020 - March 17, 2020)
In: Andreas Maier, Klaus Hermann Maier-Hein, Thomas Martin Deserno, Heinz Handels, Thomas Tolxdorff (ed.): Bildverarbeitung für die Medizin: Algorithmen – Systeme – Anwendungen 2020
URL: https://arxiv.org/abs/1911.01178
BibTeX: Download - Huang Y., Preuhs A., Lauritsch G., Manhart M., Huang X., Maier A.:
Data Consistent Artifact Reduction for Limited Angle Tomography with Deep Learning Prior
MICCAI MLMIR (Shenzhen, China, October 17, 2019 - October 17, 2019)
In: Knoll, Florian and Maier, Andreas and Rueckert, Daniel and Ye, Jong Chul (ed.): Machine Learning for Medical Image Reconstruction, Cham: 2019
DOI: 10.1007/978-3-030-33843-5_10
URL: https://link.springer.com/chapter/10.1007/978-3-030-33843-5_10
BibTeX: Download - Huang Y., Taubmann O., Huang X., Haase V., Lauritsch G., Maier A.:
A NEW WEIGHTED ANISOTROPIC TOTAL VARIATION ALGORITHM FOR LIMITED ANGLE TOMOGRAPHY
2016 IEEE 13th International Symposium on Biomedical Imaging (ISBI) (Prague, April 13, 2016 - April 16, 2016)
In: the 2016 IEEE International Symposium on Biomedical Imaging: From Nano to Macro 2016
DOI: 10.1109/ISBI.2016.7493336
URL: https://www5.informatik.uni-erlangen.de/Forschung/Publikationen/2016/Huang-ANW.pdf
BibTeX: Download