  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.
