Interactive Parts Model: An Application to Recognition of On-Line Cursive Script
Abstract
In this work, we introduce an Interactive Parts (IP) model as an alternative to Hidden Markov Models (HMMs). We tested both models on a database of on-line cursive script. We show that im(cid:173) plementations of HMMs and the IP model, in which all letters are assumed to have the same average width, give comparable results. However , in contrast to HMMs, the IP model can handle duration modeling without an increase in computational complexity.
Cite
Text
Neskovic et al. "Interactive Parts Model: An Application to Recognition of On-Line Cursive Script." Neural Information Processing Systems, 2000.Markdown
[Neskovic et al. "Interactive Parts Model: An Application to Recognition of On-Line Cursive Script." Neural Information Processing Systems, 2000.](https://mlanthology.org/neurips/2000/neskovic2000neurips-interactive/)BibTeX
@inproceedings{neskovic2000neurips-interactive,
title = {{Interactive Parts Model: An Application to Recognition of On-Line Cursive Script}},
author = {Neskovic, Predrag and Davis, Philip C. and Cooper, Leon N.},
booktitle = {Neural Information Processing Systems},
year = {2000},
pages = {974-980},
url = {https://mlanthology.org/neurips/2000/neskovic2000neurips-interactive/}
}