Name
Abstract | ||
|---|---|---|
Perceptual problems often call upon the application of a variety of knowledge sources. An automated problem solver can utilize much of this knowledge in the form of top-down guidance to improve accuracy and reduce processing time. Ironically, most automated hand-written character recognition systems, which are highly accurate, seldom use any top-down guidance. This paper describes an approach to automated hand-written character recognition that applies domain-specific knowledge such that a partial solution can be refined through top-down guidance. Specifically, the recognition task is one in which features derived from the input data are explained through higher-level hypotheses using abduction. Top-down guidance is used to improve accuracy. This approach has been applied to several domains. Individual character recognition is 70% without top-down guidance but improves to 99% with guidance. |
Year | Venue | Keywords |
|---|---|---|
2006 | IC-AI | abduction,top-down guidance.,- hand-written character recognition,iron,top down |
Field | DocType | Citations |
Character recognition,Computer science,Artificial intelligence,Natural language processing | Conference | 1 |
PageRank | References | Authors |
0.55 | 8 | 2 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Richard Fox | 1 | 4 | 2.04 |
| William Hartmann | 2 | 64 | 10.66 |