On-Line and Off-Line Handwriting Recognition: A Comprehensive Survey
IEEE Transactions on Pattern Analysis and Machine Intelligence
Behavior detection using confidence intervals of hidden Markov models
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Botnet traffic detection using hidden Markov models
Proceedings of the Seventh Annual Workshop on Cyber Security and Information Intelligence Research
P2P hierarchical botnet traffic detection using hidden Markov models
Proceedings of the 2012 Workshop on Learning from Authoritative Security Experiment Results
| Hi-index | 0.00 |
The idea of combining the network of HMMs and the dynamic programming-based search is highly relevant to online handwriting recognition. The word model of HMM network can be systematically constructed by concatenating letter and ligature HMM's while sharing common ones. Character recognition in such a network can be defined as the task of best aligning a given input sequence to the best path in the network. One distinguishing feature of the approach is that letter segmentation is obtained simultaneously with recognition but no extra computation is required