@inproceedings{INSS07C,
  author = {V Baier and L M\"{o}senlechner and Matthias Kranz},
  title = {{Gesture Classification with Hierarchically Structured Recurrent Self-Organizing Maps}},
  year = {2007},
  month = {Mar},
  abstract = {{New input devices need clever algorithms to process input information.
	We constructed a hierarchically structured neural network assembly
	based on recurrent self-organizing maps which is able to process
	and to classify motion data. We derived motion data using a so called
	Gesture Cube (M. Kranz et al., 2006), a cubic tangible user interface
	developed for one-handed control of media appliances in a home environment.
	This previously recorded data was automatically pre-processed by
	our biologically inspired neural network and classified by a improved
	k-nearest neighborhood classifier. In this paper we shortly describe
	the platform used for data acquisition but focus on the novel algorithms
	used for classification.}},
  booktitle = {Proc. Fourth International Conference on Networked Sensing Systems	INSS '07},
  doi = {10.1109/INSS.2007.4297394},
  pages = {81--84},
}