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Gesture Classification with Hierarchically Structured Recurrent Self-Organizing Maps
2007
2007 Fourth International Conference on Networked Sensing Systems
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 [1], 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
doi:10.1109/inss.2007.4297394
fatcat:nxrgqsnzwfhqrpfuus5b3yio7q