Demo Data from EDBT 2026 / reviewers in the wild / expert
E. Melnik
dblp:97/4678
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 1993
—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 · 50% Visual content generation and editing · 50% | |
| Computer architecture, parallel and distributed computing, and storage systems
1 paper |
Parallel and multicore computing · 100% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Image and video processing
document image analysis |
0.0 | 1 | 1993 | A system for automatic vectorization and interpretation of map-drawings · ICCV 1993 |
Visual content generation and editing
image vectorization |
0.0 | 1 | 1993 | A system for automatic vectorization and interpretation of map-drawings · ICCV 1993 |
Parallel and multicore computing
pipelined processing |
0.0 | 1 | 1993 | A system for automatic vectorization and interpretation of map-drawings · ICCV 1993 |
Methods — techniques the papers use, named apart from their topics
transputer chain · 0.0pipeline-oriented scheme · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 1993 | A system for automatic vectorization and interpretation of map-drawingsabstractThe authors describe a system for automatic interpretation of map-drawings. To vectorize large-size 2-D line-drawing images, an effective pipeline-oriented scheme and special techniques have been developed on the basis of economic image representation. This allows processing large-size binary images on a personal computer and obtaining satisfactory time characteristics. This approach can be easily realized in a pipelined architecture using a simple transputer chain. The document object recognition techniques are described.> Sergey Ablameyko 0001, Vladimir Bereishik, Oleg Frantskevich, Maria Homenko, E. Melnik, Oleg Okun, Nadeshda Paramonova |
ICCV | 5 |