137 citations · 184 across the 9 of their papers we have counts for
10 papers
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…
Bench-Marking Information Extraction in Semi-Structured Historical Handwritten Records
Animesh Prasad, Hervé Déjean, Jean-Luc Meunier +3
In this report, we present our findings from benchmarking experiments for information extraction on historical handwritten marriage records Esposalles from IEHHR - ICDAR 2017 robus…
System Description of CITlab's Recognition & Retrieval Engine for ICDAR2017 Competition on Information Extraction in Historical Handwritten Records
Tobias Strauß, Max Weidemann, Johannes Michael +3
We present a recognition and retrieval system for the ICDAR2017 Competition on Information Extraction in Historical Handwritten Records which successfully infers person names and o…
A Two-Stage Method for Text Line Detection in Historical Documents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This work presents a two-stage text line detection method for historical documents.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…
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…
Regular expressions for decoding of neural network outputs
Tobias Strauß, Gundram Leifert, Tobias Grüning +1
This article proposes a convenient tool for decoding the output of neural networks trained by Connectionist Temporal Classification (CTC) for handwritten text recognition. We use r…
CITlab ARGUS for Arabic Handwriting
Gundram Leifert, Roger Labahn, Tobias Strauß
In the recent years it turned out that multidimensional recurrent neural networks (MDRNN) perform very well for offline handwriting recognition tasks like the OpenHaRT 2013 evaluat…
CITlab ARGUS for historical data tables
Gundram Leifert, Tobias Grüning, Tobias Strauß +1
We describe CITlab's recognition system for the ANWRESH-2014 competition attached to the 14. International Conference on Frontiers in Handwriting Recognition, ICFHR 2014. The task…
CITlab ARGUS for historical handwritten documents
Tobias Strauß, Tobias Grüning, Gundram Leifert +1
We describe CITlab's recognition system for the HTRtS competition attached to the 14. International Conference on Frontiers in Handwriting Recognition, ICFHR 2014. The task compris…
Cells in Multidimensional Recurrent Neural Networks
G. Leifert, T. Strauß, T. Grüning +1
The transcription of handwritten text on images is one task in machine learning and one solution to solve it is using multi-dimensional recurrent neural networks (MDRNN) with conne…