Demo Data from VLDB 2026 / reviewers in the wild / expert
Oleg Frantskevich
dblp:32/4602
· DBLP profile ↗
3ranked-venue papers
0as first author
0since 2021 · last 1998
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 3Graphics, computer vision, multimedia, augmented reality and games · 2Databases, data management, data science and information retrieval · 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 |
|---|---|---|---|
| 1998 | A system for automatic recognition of engineering drawing entitiesabstractThe paper describes the VEDI (Vectorization of Engineering Drawing Images) system developed for automatic recognition of main engineering drawing (ED) entities. The main principles of ED interpretation are introduced and the algorithms to recognize main ED entities are briefly described. In conclusion, some technical parameters and experimental results of the system performance are given. Sergey Ablameyko 0001, Vladimir Bereishik, Oleg Frantskevich, Maria Homenko, Nadeshda Paramonova |
ICPR | 3 |
| 1997 | Algorithms for Recognition of the Main Engineering Drawing EntitiesabstractThe paper introduces the main principles of automatic interpretation of engineering drawing images. The technology of ED interpretation is proposed based on the introduced principles. The algorithms for automatic recognition of the main ED entities: line types, circular arcs, blocks, crosshatched areas and dimensions are proposed. They have been verified experimentally in the whole ED interpretation technology and show good results. Sergey Ablameyko 0001, Vladimir Bereishik, Oleg Frantskevich, Maria Homenko, Nadeshda Paramonova |
ICDAR | 3 |
| 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 | 3 |