| Name: | David Tschirschwitz, M.Sc. | |
| Raum: | Bauhausstraße 11, Raum 009 | |
| Telefon: | +49 (0) 36 43/58 37 23 | |
| E-Mail: | david.tschirschwitz[at]uni-weimar.de | |
| Sprechstunde: | Auf Anfrage | |
| Lehre: | Deep Learning for Computer Vision Learning Robust Object Detection with Soft-Labels from Multiple Annotators | |
| Forschung: | Human Label Variation, Object Detection, Instance Segmentation, Image Retrieval, Document Analysis and Recognition | |
Aktuelle Forschungsprojekte
- Text-Bild-Gefüge - Digital Humanities und der Diskurs der Moderne (1880-1930)
Veröffentlichungen
- M. Florek, D. Tschirschwitz, B. Barz und V. Rodehorst: Efficient and Discriminative Image Feature Extraction for Universal Image Retrieval, Pattern Recognition, DAGM GCPR 2024, Lecture Notes in Computer Science, Springer, 2024. (im Druck)
- D. Tschirschwitz, C. Benz, M. Florek, H. Norderhus, B. Stein und V. Rodehorst: Drawing the Same Bounding Box Twice? Coping Noisy Annotations in Object Detection with Repeated Labels, Pattern Recognition, DAGM GCPR 2023, Lecture Notes in Computer Science, Springer, 2023. [arxiv][doi]
- D. Tschirschwitz, F. Klemstein, H. Schmidgen und V. Rodehorst: Drawing the Line: A Dual Evaluation Approach for Shaping Ground Truth in Image Retrieval Using Rich Visual Embeddings of Historical Images, 7th International ICDAR-Workshop on Historical Document Imaging and Processing (HIP), Association for Computing Machinery, San José, USA, S. 13–18, 2023. [doi][DHMTIC][DHREAAL]
- D. Tschirschwitz, F. Klemstein, B. Stein und V. Rodehorst: A Dataset for Analysing Complex Document Layouts in the Digital Humanities and Its Evaluation with Krippendorff’s Alpha, In: B. Andres, F. Bernard, D. Cremers, S. Frintrop, B. Goldlücke, I. Ihrke (Hrsg.) Pattern Recognition, DAGM GCPR 2022, Lecture Notes in Computer Science, Vol. 13485, Springer, S. 354-374, 2022. [doi] [Paper]