Gundram   Leifert
Tobias   Grüning
Tobias   Strauß
Roger   Labahn

CITlab ARGUS for historical data tables

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 ANWRESH-2014 competition attached to the 14.International Conference on Frontiers in Handwriting Recognition, ICFHR 2014. The task comprises word recognition from segmented historical documents. The core components 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 ANWRESH-2014 Word Recognition Task

karin.martin@uni-rostock.de
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