Lexical Post-Processing Optimization for Handwritten Word Recognition
ICDAR '03 Proceedings of the Seventh International Conference on Document Analysis and Recognition - Volume 1
ICDAR '03 Proceedings of the Seventh International Conference on Document Analysis and Recognition - Volume 2
Design and integration of a handwritten character recognition system into mobile phones
UbiMob '04 Proceedings of the 1st French-speaking conference on Mobility and ubiquity computing
Statistical Language Models for On-line Handwritten Sentence Recognition
ICDAR '05 Proceedings of the Eighth International Conference on Document Analysis and Recognition
MS-TDNN with Global Discriminant Trainings
ICDAR '05 Proceedings of the Eighth International Conference on Document Analysis and Recognition
On-line Writer Adaptation for Handwriting Recognition using Fuzzy Inference Systems
ICDAR '05 Proceedings of the Eighth International Conference on Document Analysis and Recognition
IHM 2005 Proceedings of the 17th international conference on Francophone sur l'Interaction Homme-Machine
Detection and recognition of erasures in on-line captured paper forms
Pattern Recognition Letters
Pattern Recognition Strategies for Interactive Sketch Composition
Proceedings of the 13th International Conference on Human-Computer Interaction. Part II: Novel Interaction Methods and Techniques
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This paper presents the evolving of our academic development to a technology driven application: the integration of an unconstraint cursive on-line handwritten characters into a smart phone device. The ultimate goal of this work is to implement an accuracy handwritingrecognizer into mobile devices with limited computing and memory resources. A hierarchical fuzzy modeling is used to obtain a compact and robust knowledge representation and the decision process is based on an adapted fuzzy inference system to reduce computing without decreasing the peiformances. We describe in this paper the basic architecture of the recognition system called "ResifCar", its practical adaptation to the mobile device constraintsand the recognition rates both on cursive isolated letters (91.9%) and on isolated digits (92.3%) in a writer independent context based on 100 different writers.