Profil Thomas Stephani

Schwerpunkte/Kompetenzen

• CNNs with Limited Amount of Training Data
• Markov Random Field Models for Computer Vision
• Visual Correspondence Estimation (Stereo, Motion)
• Photomontage, Stitching
• Projective Geometry
• Software Development in C++ / Matlab

Publikationen

Highlightpublikationen

• Stephani, H.; Weibel, T.; Rösch, R.; Moghiseh, A.:
  Machine Learning for Inline Surface Inspection Systems: Challenges, Approaches, and Application Example.
  In: Franke, J., Schöbel, A. (eds) Statistical Machine Learning for Engineering with Applications. Lecture Notes in Statistics, vol 227, 2024.
  Springer, Cham. https://doi.org/10.1007/978-3-031-66253-9_2
• Nieradzik, L.; Sieburg-Rockel, J.; Helmling, S.; Keuper, J.; Weibel, T.; Olbrich, A. and Stephani, H.:
  Automating Wood Species Detection and Classification in Microscopic Images of Fibrous Materials with Deep Learning.
  arXiv preprint arXiv:2307.09588. (2023)
• 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)
• 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.
• S. Ali, C. Daul, T. Weibel, and W. Blondel: 
  Fast mosaicing of cystoscopic images from dense correspondence: combined SURF and TV-L1 optical flow method. 
  In 20th International Conference on Image Processing (ICIP), pages 1291-1295, September 2013. Melbourne, Australien.
• T. Weibel, C. Daul, D. Wolf, R. Rösch, and F. Guillemin:
  Graph based construction of textured large field of view mosaics for bladder cancer diagnosis. 
  Pattern Recognition, 45(12):4138 – 4150, 2012
• T. Weibel, C. Daul, D. Wolf, and R. Rösch: 
  Contrast-enhancing seam detection and blending using graph cuts. 
  In 21st International Conference on Pattern Recognition (ICPR), pages 2732–2735, November 2012. Tsukuba, Japan (Oral presentation).