A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2017; you can also visit the original URL.
The file type is
This paper describes a mode detection system for online pen input that employs a Bayesian network to combine classification results and context information. Previous monolithic classifiers were not able to provide sufficient performance to be used in the domain of crisis management, where robust interaction is extremely important. To enhance mode detection for the intended target domain of crisis management, domain specific pen gesture data was used to train the four different classifiers anddoi:10.1109/icdar.2007.4377039 dblp:conf/icdar/WillemsV07 fatcat:yihfsglatrcudbctingzkihpl4