Name
Title | ||
|---|---|---|
Evidential combination of multiple HMM classifiers for multi-script handwriting recognition |
Abstract | ||
|---|---|---|
In this work, we focus on an improvement of a multiscript handwritting recognition system using a HMM based classifiers combination. The improvement relies on the use of Dempster-Shafer theory to combine in a finer way the probabilistic outputs of the HMM classifiers. The experiments are conducted on two public databases written on two different scripts : IFN/ENIT (latin script) and RIMES (arabic script). The obtained results are compared with the classical algorithms of the field and the superiority of the proposed approach is shown. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1007/978-3-642-14049-5_46 | IPMU |
Keywords | Field | DocType |
hmm classifier,classical algorithm,evidential combination,different script,dempster-shafer theory,multiscript handwritting recognition system,classifiers combination,arabic script,multiple hmm classifier,probabilistic output,multi-script handwriting recognition,latin script,dempster shafer theory,handwriting recognition | Borda count,Recognition system,Computer science,Handwriting recognition,Speech recognition,Latin script,Artificial intelligence,Probabilistic logic,Hidden Markov model,Machine learning,Scripting language,Arabic script | Conference |
ISBN | Citations | PageRank |
3-642-14048-3 | 5 | 0.45 |
References | Authors | |
10 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yousri Kessentini | 1 | 100 | 15.39 |
| Thomas Burger | 2 | 38 | 5.81 |
| Thierry Paquet | 3 | 565 | 56.65 |