Demo Data from SIGIR 2026 / reviewers in the wild / expert
Philippe Garnesson
dblp:99/4510
· DBLP profile ↗
2ranked-venue papers
2as first author
0since 2021 · last 1990
0000-0002-5959-1293ORCID · corroborated
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 2 · 2 first-authorGraphics, computer vision, multimedia, augmented reality and games · 2 · 2 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 |
Segmentation and scene understanding · 100% |
Topics — the 1 heaviest of 1, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Computer vision › Segmentation and scene understanding › context modeling
spatial context |
0.0 | 1 | 1990 | Spatial Context In An Image Analysis System · ECCV 1990 |
| Year | Publication | Venue | Position |
|---|---|---|---|
| 1990 | Spatial Context In An Image Analysis System
Philippe Garnesson, Gérard Giraudon |
ECCV | 1 |
| 1990 | An image analysis, application for aerial imagery interpretationabstractThe architecture of an image analysis system called MESSIE (Multi Expert System for Scene Interpretation and Evaluation) is presented. This system reasons from geometric models which are represented by four concepts (geometry, radiometry, context, and function). The aim is to find the class instances from the generic models which are present in the scene. The necessity of having a hierarchic and opportunistic method of solving the problem of interpretation is shown. In a first step, MESSIE tries to detect salient objects. Then, using characteristics of salient objects and knowledge about the context of objects, MESSIE tries to confirm the object hypothesis and to infer new objects in the scene. The domain used to develop MESSIE is aerial imagery interpretation. Results on the detection of roads and buildings in suburban images are given.> Philippe Garnesson, Gérard Giraudon, Philippe Montesinos |
ICPR (1) | 1 |