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In computer science, geometric hashing is a method for efficiently finding two-dimensional objects represented by discrete points that have undergone an affine transformation, though extensions exist to other object representations and transformations. In an off-line step, the objects are encoded by treating each pair of points as a geometric basis. The…
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basis points object hashing geometric table image coordinates hash objects pair data recognition point step feature two selected candidate computer
| Subject | Predicate | Object | Confidence | Src |
|---|---|---|---|---|
| Geometric hashing | is a | method for efficiently finding two-dimensional objects represented by discrete points that have undergone an affine transformation | 0.90 | text |
| structural alignment of proteins | instance of | but later was applied to different problems | 0.80 | text |
| SIFT could be used for indexing | instance of | in practice local descriptors | 0.80 | text |
| Geometric hashing | related to Finding mirrored pattern | It | 0.60 | section |
| Geometric hashing | related to Finding mirrored pattern | However | 0.60 | section |
| Geometric hashing | related to Finding mirrored pattern | Therefore | 0.60 | section |
| Geometric hashing | related to Finding mirrored pattern | There | 0.60 | section |
| Geometric hashing | related to Finding mirrored pattern | For | 0.60 | section |
| Geometric hashing | related to Finding mirrored pattern | Multiplying | 0.60 | section |
| Geometric hashing | related to Finding mirrored pattern | Use | 0.60 | section |
| Geometric hashing | related to Finding mirrored pattern | This | 0.60 | section |
| Geometric hashing | related to Finding mirrored pattern | Actually | 0.60 | section |
These clusters group vocabulary that occurs around closely connected concepts in the source material.
Bridges can reveal useful research angles that are easy to miss in a flat list of related terms.