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  4. Precision Learning

Precision Learning

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Precision Learning

Contact

Christopher Syben

Dr. Christopher Syben, M. Sc.

Researcher

Department of Computer Science
Chair of Computer Science 5 (Pattern Recognition)

Room: Room 09.132
Martensstr. 3
91058 Erlangen
  • Phone number: +49 9131 85-27874
  • Email: christopher.syben@fau.de
  • Website: https://lme.tf.fau.de/person/syben/
Bernhard Stimpel

Bernhard Stimpel, M. Sc.

Researcher

Department of Computer Science
Chair of Computer Science 5 (Pattern Recognition)

Room: Room 09.132
Martensstr. 3
91058 Erlangen
  • Phone number: +49 9131 85-27874
  • Email: bernhard.stimpel@fau.de
  • Website: http://www5.cs.fau.de/~stimpel
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.

Projects

Participating Scientists

Publications

  • 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 X., Yang H., Huang Y., Shi L., He F., Maier A., Yan M.:
    Robust mixed one-bit compressive sensing
    In: Signal Processing 162 (2019), p. 161-168
    ISSN: 0165-1684
    DOI: 10.1016/j.sigpro.2019.04.011
    BibTeX: Download
  • Huang Y., Taubmann O., Huang X., Hornegger J., Lauritsch G., Maier A.:
    Restoration of Missing Data in Limited Angle Tomography Based on Consistency Conditions
    The 14th International Meeting on Fully Three‐Dimensional Image Reconstruction in Radiology and Nuclear Medicine (Xi'an, China, June 18, 2017 - June 23, 2017)
    In: Ge Wang and Xuanqin Mou (ed.): The 14th International Meeting on Fully Three‐Dimensional Image Reconstruction in Radiology and Nuclear Medicine 2017
    URL: https://www5.informatik.uni-erlangen.de/Forschung/Publikationen/2017/Huang17-ROM.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
  • 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
Friedrich-Alexander-Universität
Erlangen-Nürnberg

Schlossplatz 4
91054 Erlangen
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