5 papers · 1 filter
End-To-End Measure for Text Recognition
Gundram Leifert, Roger Labahn, Tobias Grüning +1
Measuring the performance of text recognition and text line detection engines is an important step to objectively compare systems and their configuration. There exist well-establis…
Evaluating Sequence-to-Sequence Models for Handwritten Text Recognition
Johannes Michael, Roger Labahn, Tobias Grüning +1
Encoder-decoder models have become an effective approach for sequence learning tasks like machine translation, image captioning and speech recognition, but have yet to show competi…
A Two-Stage Method for Text Line Detection in Historical Documents
Tobias Grüning, Gundram Leifert, Tobias Strauß +2
This work presents a two-stage text line detection method for historical documents. Each detected text line is represented by its baseline. In a first stage, a deep neural network…
READ-BAD: A New Dataset and Evaluation Scheme for Baseline Detection in Archival Documents
Tobias Grüning, Roger Labahn, Markus Diem +2
Text line detection is crucial for any application associated with Automatic Text Recognition or Keyword Spotting. Modern algorithms perform good on well-established datasets since…
CITlab ARGUS for historical handwritten documents
Gundram Leifert, Tobias Strauß, Tobias Grüning +1
We describe CITlab's recognition system for the HTRtS competition attached to the 13. International Conference on Document Analysis and Recognition, ICDAR 2015. The task comprises…