Application of Adaptive Committee Classifiers in On-Line Character Recognition
ICAPR '01 Proceedings of the Second International Conference on Advances in Pattern Recognition
The Recognition Graph - Language Independent Adaptable On-line Cursive Script Recognition
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
Minimum Classification Error Training for Online Handwriting Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
ACM SIGGRAPH 2007 courses
Lightweight user-adaptive handwriting recognizer for resource constrained handheld devices
Proceeding of the workshop on Document Analysis and Recognition
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We have developed an adaptive on-line recognizer suitable for recognizing isolated alphanumeric characters. It is based on the $k$ nearest neighbor rule. Various dissimilarity measures, all based on dynamic time warping (DTW), have been studied. The main focus of the work is on on-line adaptation. The adaptation is performed by modifying the prototype set of the classifier according to its recognition performance and the user's writing style. These adaptations include: 1) adding new prototypes, 2) inactivating confusing prototypes, and 3) reshaping existing prototypes. The reshaping algorithm is based on Learning Vector Quantization (LVQ). The writers are allowed to use their own natural style of writing, and the adaptation is carried out during normal use in a self-supervised fashion and thus remains otherwise unnoticed by the user.