  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historical documents.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.
