Demo Data from VLDB 2026 / reviewers in the wild / expert
John W. Gorman
dblp:09/6512
· DBLP profile ↗
1ranked-venue papers
1as first author
0since 2021 · last 1988
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 1 · 1 first-author
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.
| Artificial intelligence
1 paper |
Image recognition and object detection · 100% | |
| Theoretical computer science
1 paper |
Algorithms and data structures · 100% |
Topics — the 4 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Computer vision › Image recognition and object detection › shape recognition
partial shape recognition |
0.0 | 1 | 1988 | Partial Shape Recognition Using Dynamic Programming · IEEE Trans. Pattern Anal. Mach. Intell. 1988 |
Computer vision › Image recognition and object detection
shape recognition |
0.0 | 1 | 1988 | Partial Shape Recognition Using Dynamic Programming · IEEE Trans. Pattern Anal. Mach. Intell. 1988 |
Algorithms and data structures
dynamic programming |
0.0 | 1 | 1988 | Partial Shape Recognition Using Dynamic Programming · IEEE Trans. Pattern Anal. Mach. Intell. 1988 |
Algorithms and data structures › sequence algorithms › string algorithms
sequence comparison |
0.0 | 1 | 1988 | Partial Shape Recognition Using Dynamic Programming · IEEE Trans. Pattern Anal. Mach. Intell. 1988 |
Methods — techniques the papers use, named apart from their topics
dynamic programming · 0.0fourier descriptors · 0.0fourier descriptor · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 1988 | Partial Shape Recognition Using Dynamic ProgrammingabstractA partial-shape-recognition technique utilizing local features described by Fourier descriptors is introduced. A dynamic programming formulation for shape matching is developed, and a method for comparison of match quality is discussed. This technique is shown to recognize unknown contours that may be occluded or that may overlap other objects. Precise scale information is not required, and the unknown objects may appear at any orientation with respect to the camera. The segment-matching dynamic programming method is contrasted with other sequence-comparison techniques that utilize dynamic programming. Experimental results are discussed that indicate that partial contours can be recognized with reasonable accuracy.> John W. Gorman, Owen Robert Mitchell, Frank P. Kuhl |
IEEE Trans. Pattern Anal. Mach. Intell. | 1 |