Precision Learning

Precision Learning is a research direction, seeking
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.

• Huang Y., Taubmann O., Huang X., Lauritsch G., Maier A.:
  Papoulis-Gerchberg Algorithms for Limited Angle Tomography Using Data Consistency Conditions
  the 5th International Conference on Image Formation in X-ray Computed Tomography (Salt Lake City, Utah, the USA, May 20, 2018 - May 23, 2018)
  In: Proceedings of the 5th International Conference on Image Formation in X-ray Computed Tomography, Salt Lake City, Utah, the USA: 2018
  URL: https://www5.informatik.uni-erlangen.de/Forschung/Publikationen/2018/Huang18-PAF.pdf
  BibTeX: Download
• Huang Y., Huang X., Taubmann O., Xia Y., Haase V., Hornegger J., Lauritsch G., Maier A.:
  Restoration of Missing Data in Limited Angle Tomography Based on Helgason-Ludwig Consistency Conditions
  In: Biomedical Physics and Engineering Express 3 (2017), p. 035015
  ISSN: 2057-1976
  DOI: 10.1088/2057-1976/aa71bf
  URL: https://www5.informatik.uni-erlangen.de/Forschung/Publikationen/2017/Huang17-ROM.pdf
  BibTeX: Download
• 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 Y., Taubmann O., Huang X., Haase V., Lauritsch G., Maier A.:
  Scale-Space Anisotropic Total Variation for Limited Angle Tomography
  In: IEEE Transactions on Radiation and Plasma Medical Sciences 2 (2018), p. 307-314
  ISSN: 2469-7311
  DOI: 10.1109/TRPMS.2018.2824400
  URL: https://www5.informatik.uni-erlangen.de/Forschung/Publikationen/2018/Huang18-SAT.pdf
  BibTeX: Download
• Huang Y., Lu Y., Taubmann O., Lauritsch G., Maier A.:
  Traditional machine learning for limited angle tomography
  In: International Journal of Computer Assisted Radiology and Surgery 8/2018 (2018), p. 1-9
  ISSN: 1861-6410
  DOI: 10.1007/s11548-018-1851-2
  URL: https://www5.informatik.uni-erlangen.de/Forschung/Publikationen/2018/Huang18-TML_IJCARS.pdf
  BibTeX: Download