Name
Abstract | ||
|---|---|---|
This paper presents a novel segmentation-based and lexicon-driven handwritten English recognition systems. For the segmentation, a modified online segmentation method based on rules are applied. Then, convolutional neural networks are introduced for offline character recognition. Experiments are evaluated on UNIPEN lowercase data sets, with the word recognition rate of 92.20%. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1109/ICFHR.2012.210 | ICFHR |
Keywords | Field | DocType |
segmentation-based handwritten english word recognition system,convolutional neural networks,unipen lowercase data set,image segmentation,handwritten english word recognition,convolution,convolutional neural network,word recognition rate,lexicon-driven handwritten english recognition system,lexicon-driven handwritten english recognition,online segmentation,handwritten character recognition,natural language processing,modified word segmentation,modified online segmentation method,neural nets,offline character recognition | Neocognitron,Pattern recognition,Intelligent character recognition,Segmentation,Convolutional neural network,Computer science,Word recognition,Image segmentation,Speech recognition,Artificial intelligence,Artificial neural network,Intelligent word recognition | Conference |
ISSN | ISBN | Citations |
2167-6445 | 978-1-4673-2262-1 | 8 |
PageRank | References | Authors |
0.57 | 6 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Aiquan Yuan | 1 | 18 | 1.15 |
| Gang Bai | 2 | 9 | 1.60 |
| Po Yang | 3 | 15 | 1.49 |
| Yan-Ni Guo | 4 | 8 | 1.58 |
| Xinting Zhao | 5 | 8 | 0.57 |