Name
Abstract | ||
|---|---|---|
We present a promising new framework for improving boosting performance with transductive inference when training an automatic text detector. The resulting detector is fast and efficient, and it exhibits high accuracy on a large test set. |
Year | DOI | Venue |
|---|---|---|
2005 | 10.1109/ICDAR.2005.59 | ICDAR-1 |
Keywords | Field | DocType |
document image processing,inference mechanisms,learning (artificial intelligence),text analysis,automatic text detector,boosting-based transductive learning,text detection,transductive inference | Transduction (machine learning),Text mining,Semi-supervised learning,Pattern recognition,Document image processing,Computer science,Artificial intelligence,Boosting (machine learning),Detector,Machine learning,Text detection,Test set | Conference |
ISSN | ISBN | Citations |
1520-5263 | 0-7695-2420-6 | 7 |
PageRank | References | Authors |
0.55 | 5 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| David Bargeron | 1 | 7 | 0.55 |
| Paul Viola | 2 | 12742 | 1194.92 |
| Patrice Y. Simard | 3 | 1112 | 155.00 |