Demo Data from SIGIR 2026 / reviewers in the wild / expert
Carl Smets
dblp:135/1934
· DBLP profile ↗
2ranked-venue papers
1as first author
0since 2021 · last 1989
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 2 · 1 first-authorGraphics, 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.
| Interdisciplinary, comprehensive, and emerging computing
1 paper |
Medical and health informatics · 100% | |
| Artificial intelligence
1 paper |
3D vision · 100% | |
| Computer graphics and multimedia
1 paper |
Multimedia analysis and retrieval · 100% |
Topics — the 4 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Computer vision › 3D vision › stereo vision
stereo matching |
0.0 | 1 | 1989 | Recognition of the coronary blood vessels on angiograms using hierarchical model-based iconic search · CVPR 1989 |
Medical and health informatics › medical imaging › vascular imaging
coronary angiography |
0.0 | 1 | 1989 | Recognition of the coronary blood vessels on angiograms using hierarchical model-based iconic search · CVPR 1989 |
Medical and health informatics › medical imaging
medical image analysis |
0.0 | 1 | 1989 | Recognition of the coronary blood vessels on angiograms using hierarchical model-based iconic search · CVPR 1989 |
Multimedia analysis and retrieval › object recognition
model-based recognition |
0.0 | 1 | 1989 | Recognition of the coronary blood vessels on angiograms using hierarchical model-based iconic search · CVPR 1989 |
Methods — techniques the papers use, named apart from their topics
stereoscopic matching · 0.0iconic search · 0.0hierarchical model · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 1989 | Recognition of the coronary blood vessels on angiograms using hierarchical model-based iconic searchabstractThe recognition of the coronary blood vessels on single angiograms is addressed. Recognizing blood vessels on digital subtraction angiograms is a prerequisite to automatic diagnosis and quantification of blood-vessel pathologies. It is shown how stereoscopic angiograms can improve the interpretation process. The computational strategy recommended to solve the problem has the following important characteristics. First, the model is hierarchically instantiated, starting from a partial model and working up to the final complete model. Second, the contact with the image is never broken during the interpretation process. Missing model attributes are instantiated by returning to the image. Third, delineation (segmentation and image partitioning), interpretation, and stereoscopic matching are not sequential but integrated processes. Fourth, the knowledge representation is partially iconic. The iconic memory is used to guide the search for missing or incomplete attributes in the image.> Paul Suetens, Carl Smets, Frans Van de Werf, André Oosterlinck |
CVPR | 2 |
| 1988 | A knowledge-based system for the delineation of blood vessels on subtraction angiograms
Carl Smets, Geert Verbeeck, Paul Suetens, André Oosterlinck |
Pattern Recognit. Lett. | 1 |