Peer reviewed journal papers

  • Dorozynski M., Rottensteiner F. (2022): Deep descriptor learning with auxiliary classification loss for retrieving images of silk fabrics in the context of preserving European silk heritage. ISPRS International Journal of Geo-Information 11(2), paper 82
    DOI: 10.3390/ijgi11020082
  • Rei, L.; Mladenic, D.; Dorozynski, M.; Rottensteiner, F.; Schleider, T.; Troncy, R.; Sebastián Lozano, J.; Gaitán Salvatella, M. (2022): Multimodal metadata assignment for cultural heritage artifacts, In: Multimedia Systems, 1-23.
    DOI: 10.1007/s00530-022-01025-2
  • Alba Pagán, E.; Gaitán Salvatella, M.; Pitarch, M. D.; León Muñoz, A.; Moya Toledo, M.; Marin Ruiz, J.; Vitella, M.; Lo Cicero, G.; Rottensteiner, F.; Clermont, D.; Dorozynski, M.; Wittich , D.; Vernus, P.; Puren, M. (2020): From silk to digital technologies: A gateway to new opportunities for creative industries, traditional crafts and designers. The SILKNOW case, In: Sustainability 12(19), paper 8279. More info
    DOI: 10.3390/su12198279

Peer reviewed conference papers

  • Schleider T., Troncy R., Ehrhart T., Dorozynski M., Rottensteiner F., Sebastián Lozano J., Lo Cicero, G. (2021): Searching silk fabrics by images leveraging on knowledge graph and domain expert rules. In: SUMAC'21: Proceedings of the 3rd Workshop on Structuring and Understanding of Multimedia heritAge, pp. 41–49.
  • Clermont, D.; Dorozynski, M.; Wittich, D.; Rottensteiner, F. (2020): Assessing the semantic similarity of images of silk fabrics using convolutional neural networks. In: ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences V-2, pp. 641–648. More info
    DOI: 10.5194/isprs-annals-V-2-2020-641-2020
  • Dorozynski, M.; Clermont, D.; Rottensteiner, F. (2019): Multi-task deep learning with incomplete training samples for the image-based prediction of variables describing silk fabrics. In: ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences IV-2/W6, pp. 47–54.
    DOI: 10.5194/isprs-annals-IV-2-W6-47-2019

Non-reviewed conference papers

  • Ali, R., Dorozynski, M., Stracke, J., and Mehltretter, M. (2022): DEEP LEARNING-BASED TRACKING OF MULTIPLE OBJECTS IN THE CONTEXT OF FARM ANIMAL ETHOLOGY, Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B2-2022, 509–516
    DOI: 10.5194/isprs-archives-XLIII-B2-2022-509-2022
  • Dorozynski, M. and Rottensteiner, F. (2022): ADDRESSING CLASS IMBALANCE IN MULTI-CLASS IMAGE CLASSIFICATION BY MEANS OF AUXILIARY FEATURE SPACE RESTRICTIONS , Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B2-2022, 777–785
    DOI: 10.5194/isprs-archives-XLIII-B2-2022-777-2022
  • Dorozynski, M.; Wittich, D.; Rottensteiner, F., Clermont, D. (2021): Artificial intelligence meets cultural heritage: image classification for the prediction of semantic properties of silk fabrics. Weaving Europe. Silk Heritage and Digital Technologies, ISBN 978-84-18656-97-2, pp.147-166, Tirant lo Blanch, Valencia (Spain) More info
  • Dorozynski, M.; Wittich, D.; Rottensteiner, F. (2019): Deep Learning zur Analyse von Bildern von Seidenstoffen für Anwendungen im Kontext der Bewahrung des kulturellen Erbes. 39. Wissenschaftlich-Technische Jahrestagung der DGPF und Dreiländertagung der OVG, DGPF und SGPF in Wien, Publikationen der DGPF Band 28, 387-399. More info