Demo Data from EDBT 2026 / reviewers in the wild / expert
G. B. John Mancini
dblp:200/1978
· DBLP profile ↗
1ranked-venue papers
0as 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 · 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.
| Interdisciplinary, comprehensive, and emerging computing
1 paper |
Medical and health informatics · 100% | |
| Artificial intelligence
1 paper |
Knowledge representation and reasoning · 100% |
Topics — the 2 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Medical and health informatics › medical imaging
medical image analysis |
0.0 | 1 | 1989 | Knowledge-guided left ventricular boundary detection · CVPR 1989 |
Knowledge, reasoning and agents › Knowledge representation and reasoning › cognitive modeling › cognitive architecture
blackboard architecture |
0.0 | 1 | 1989 | Knowledge-guided left ventricular boundary detection · CVPR 1989 |
Methods — techniques the papers use, named apart from their topics
opportunistic problem-solving · 0.0knowledge-based image interpretation · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 1989 | Knowledge-guided left ventricular boundary detectionabstractInterpolation of X-ray motion pictures of the heart (cineventiculograms of the left ventricle) is complicated by the low contrast of the images and the elastic motion of the heart. Here, the problem of placing the heart boundary in each frame of the motion sequence is described by a framework for the application of knowledge in the form of diagnostically relevant models of the heart in motion. A blackboard architecture is utilized as a basis for the image interpretation. In this architecture, local features such as edges are grouped to build a complete description of the moving heart; the knowledge is organized in a hierarchy with knowledge sources (KSs) operating on different levels of the hierarchy and opportunistic problem-solving techniques are used to control the order of activation of both data-directed and goal-driven sources.> Saeid Tehrani, Terry E. Weymouth, G. B. John Mancini |
CVPR | 3 |