EDBT 2026 Demo / reviewers in the wild / expert
Mateusz Ochal
dblp:263/7021
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2022
0000-0003-3799-5921ORCID · reported
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 1 · 1 since 2021Graphics, computer vision, multimedia, augmented reality and games · 1 · 1 since 2021
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 |
Image recognition and object detection · 77% Efficient and distributed learning · 23% |
Topics — the 2 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Computer vision › Image recognition and object detection › object detection › multi-object detection
dense object detection |
0.6 | 1 | 2022 | Prediction-Guided Distillation for Dense Object Detection · ECCV (9) 2022 |
Machine learning › Efficient and distributed learning › model compression
knowledge distillation |
0.2 | 1 | 2022 | Prediction-Guided Distillation for Dense Object Detection · ECCV (9) 2022 |
Methods — techniques the papers use, named apart from their topics
knowledge distillation · 0.6
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2022 | Prediction-Guided Distillation for Dense Object Detection
Chenhongyi Yang, Mateusz Ochal, Amos J. Storkey, Elliot Crowley |
ECCV (9) | 2 |