Name
Abstract | ||
|---|---|---|
Lazy evaluation is a best-first state space search method for contextual handwriting recognition which searches an ordered space and applies constraints at the earliest possible opportunity to maximize computational efficiency. Lazy evaluation is well-suited to multi-level hypothesis verification because it operates recursively on a hierarchical semantic tree of context constraints. This paper describes the lazy evaluation algorithm in detail, and proves that, if ordered hypotheses for the lowest-level sub-patterns are provided as inputs, and the combined belief function is monotonic, then overall interpretations are guaranteed to be generated in best-first order. Applications of lazy evaluation to post code dictionary and address recognition problems are outlined as illustrations of the algorithm. |
Year | DOI | Venue |
|---|---|---|
1999 | 10.1109/ICDAR.1999.791856 | Bangalore |
Keywords | Field | DocType |
lazy evaluation,context constraint,contextual handwriting recognition,computational efficiency,best-first state space search,best-first contextual handwriting recognition,combined belief function,address recognition problem,lazy evaluation algorithm,code dictionary,best-first order,algorithm design and analysis,handwriting recognition,image recognition,dictionaries,optical character recognition,first order,state space | Computer science,Handwriting recognition,Artificial intelligence,Recursion,Computer vision,Monotonic function,Intelligent character recognition,Pattern recognition,Lazy evaluation,Optical character recognition,State space search,Hypothesis verification,Machine learning | Conference |
ISBN | Citations | PageRank |
0-7695-0318-7 | 0 | 0.34 |
References | Authors | |
1 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Andy C. Downton | 1 | 121 | 31.49 |
| S. M. Lucas | 2 | 255 | 16.38 |
| Du, L. | 3 | 0 | 0.34 |