Tobias   Strauß
Tobias   Grüning
Gundram   Leifert
Roger   Labahn

CITlab ARGUS for historical handwritten documents

Preprint series:   Preprints aus dem Institut für Mathematik, Universität Rostock

MSC: 68T10   Pattern recognition, speech recognition {For cluster analysis, see 62H30}
  68T05   Learning and adaptive systems {See also 68Q32, 91E40}

Abstract:   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 comprises the recognition of historical handwritten documents.
The core algorithms of our system are based on multi-dimensional recurrent neural networks (MDRNN) and connectionist temporal classification (CTC).
The software modules behind that as well as the basic utility technologies are essentially powered by PLANET's ARGUS framework for intelligent text recognition and image processing.

Keywords:   MDRNN, LSTM, CTC, handwriting recognition, neural network
Notes:   Description of CITlab's System for the HTRtS 2014 Handwritten Text Recognition Task

karin.martin@uni-rostock.de
Seite generiert am 06.05.2014,   09:32   Uhr