1 citations · 1 across the 12 of their papers we have counts for
6 papers · 2 filters
ClapperText: A Benchmark for Text Recognition in Low-Resource Archival Documents
Tingyu Lin, Marco Peer, Florian Kleber +1
This paper presents ClapperText, a benchmark dataset for handwritten and printed text recognition in visually degraded and low-resource settings. The dataset is derived from 127 Wo…
CTC Transcription Alignment of the Bullinger Letters: Automatic Improvement of Annotation Quality
Marco Peer, Anna Scius-Bertrand, Andreas Fischer
Handwritten text recognition for historical documents remains challenging due to handwriting variability, degraded sources, and limited layout-aware annotations. In this work, we a…
Few-Shot Segmentation of Historical Maps via Linear Probing of Vision Foundation Models
Rafael Sterzinger, Marco Peer, Robert Sablatnig
As rich sources of history, maps provide crucial insights into historical changes, yet their diverse visual representations and limited annotated data pose significant challenges f…
Transparency Techniques for Neural Networks trained on Writer Identification and Writer Verification
Viktoria Pundy, Marco Peer, Florian Kleber
Neural Networks are the state of the art for many tasks in the computer vision domain, including Writer Identification (WI) and Writer Verification (WV). The transparency of these…
Assessing the impact of Binarization for Writer Identification in Greek Papyrus
Dominic Akt, Marco Peer, Florian Kleber
This paper tackles the task of writer identification for Greek papyri. A common preprocessing step in writer identification pipelines is image binarization, which prevents the mode…
Towards the Influence of Text Quantity on Writer Retrieval
Marco Peer, Robert Sablatnig, Florian Kleber
This paper investigates the task of writer retrieval, which identifies documents authored by the same individual within a dataset based on handwriting similarities. While existing…