Profil Ali Moghiseh

Schwerpunkte/Kompetenzen

  • Image Analysis
  • Machine Learning
  • Multiscale and Wavelet Approximation
  • Linear and Nonlinear Programming
  • Quantum Image Processing

 

Publikationen

Highlightpublikationen

  • Geng, A.; Moghiseh, A.; Redenbach, C.; Schladitz, K.:
    Quantum image processing on real superconducting and trapped-ion based quantum computers.
    tm-Technisches Messen, vol. 90, no. 7-8, 2023, pp. 445-454.
  • Stephani, H.; Weibel, T.; Rösch, R.; Moghiseh, A.:
    Challenges and approaches when realizing online surface inspection systems with deep learning algorithms.
    Discover Data: Volume 1, Article number: 3 (2023)
  • Geng, A.; Moghiseh, A.; Redenbach, C.; Schladitz, K.:
    A hybrid quantum image edge detector for the NISQ era.
    Quantum Machine Intelligence, Volume 4, Article number: 15 (2022).
  • Müller, O.; Fend, C.; Moghiseh, A.; Schladitz, K.; Stephani, H.; Weibel, T.:
    Deep learning for image based shelve inventories.
    10th International Symposium on Signal, Image, Video and Communications, ISIVC 2020: Saint-Etienne, France, 7–9 April 2021. Piscataway, NJ: IEEE, 2021.
  • Fend, C.; Moghiseh, A.; Redenbach, C.; Schladitz, K.:
    Reconstruction of highly porous structures from FIB-SEM using a deep neural network trained on synthetic images.
    Journal of Microscopy, 281, Nr. 1, pp. 16-27, 2021.
  • Moghiseh, A.; Schladitz, K.; Schlarb, A. K.; Suksut, B.:
    Image analytical determination of the spherulite growth in polypropylene composite.
    Image, analysis & stereology 37 (2018), No.2, pp.139-144
  • Ohser, J.; Redenbach, C.; Moghiseh, A.:
    The PPI Value of Open Foams and its Estimation by Image Analysis.
    International Journal of Materials Research, 105, 671-678, (2014)
  • Lehmann, M.; Eisengräber-Pabst, J.; Ohser, J.; Moghiseh, A.:
    Characterization of the Formation of Filter Paper using the Bartlett Spectrum of the Fiber Structure.
    Image Analysis & Stereology, vol.32:77-87, (2013)

Sammlung der Publikationen von Ali Moghiseh in der Fraunhofer-Publica