David Tschirschwitz

Name:David Tschirschwitz, M.Sc.
Room:Bauhausstraße 11, room 009
Phone:+49 (0) 36 43/58 37 23
E-Mail:david.tschirschwitz[at]uni-weimar.de
Office Hours:On request
Teaching:

Deep Learning for Computer Vision

Learning Robust Object Detection with Soft-Labels from Multiple Annotators

Applied Deep Learning for Computer Vision

Research:Human Label Variation, Object Detection, Instance Segmentation, Image Retrieval, Document Analysis and Recognition



Ongoing Research

Publications

  • M. Florek, D. Tschirschwitz, B. Barz and V. Rodehorst: Efficient and Discriminative Image Feature Extraction for Universal Image Retrieval, Pattern Recognition, DAGM GCPR 2024, Lecture Notes in Computer Science, Springer, 2024. (in press)
  • D. Tschirschwitz, C. Benz, M. Florek, H. Norderhus, B. Stein and 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 and 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Ground Truth in Image Retrieval Using Rich Visual Embeddings of Historical Images, 7th International ICDAR-Workshop on Historical Document Imaging and Processing (HIP), Association for Computing Machinery, San José, USA, S. 13–18, 2023.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 and 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 (Eds.) Pattern Recognition, DAGM GCPR 2022, Lecture Notes in Computer Science, vol. 13485, Springer, pp. 354-374, 2022. [doi] [Paper]