Demo Data from EDBT 2026 / reviewers in the wild / expert
R. Nishimura
dblp:42/5148
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 1990
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 1Graphics, computer vision, multimedia, augmented reality and games · 1
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Computer graphics and multimedia
1 paper |
Image and video processing · 100% |
Topics — the 2 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Image and video processing › pattern detection
curve detection |
0.0 | 1 | 1990 | Robust curve detection by temporal geodesics · ICCV 1990 |
Image and video processing
parallel image processing |
0.0 | 1 | 1990 | Robust curve detection by temporal geodesics · ICCV 1990 |
Methods — techniques the papers use, named apart from their topics
velocity field · 0.0graph merging · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 1990 | Robust curve detection by temporal geodesicsabstractThe formation of temporal geodesics (i.e., fast routes) in a velocity field seems to offer a means of detecting curves by parallel hardware in a wide range of images with little prior design information. This hypothesis was tested by devising and constructing a dotted-curve detector based on it, and applying the detector to several synthetic dotted images covering a wide range of dotted curves and dotted partially coherent noise. The results are encouraging. The dotted-curve detector searches for fast routes in a velocity field determined locally by the approximate collinearity or cocircularity of clusters of dots, and globally by the tortuousness of the route and the uniformity of the spacing of dots along the route. The routes are found by a parallel adaptive classification of the dots into curve dots and noise dots, followed by a parallel merging and splitting of graphs spanning temporal close dots or subgraphs at successively higher levels of abstraction.> Dan Gutfinger, R. Nishimura, H. Doi, Jack Sklansky |
ICCV | 2 |