Demo Data from EDBT 2026 / reviewers in the wild / expert
Kuang-Chern Ng
dblp:43/3074
· DBLP profile ↗
1ranked-venue papers
1as first author
0since 2021 · last 2001
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 1 · 1 first-authorSystems, architecture and hardware · 1 · 1 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.
| Computer graphics and multimedia
1 paper |
Computational photography and imaging · 56% Image and video coding · 44% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Computational photography and imaging › image acquisition › imaging system design › camera design
autofocus |
0.0 | 1 | 2001 | Practical Issues in Pixel-Based Autofocusing for Machine Vision · ICRA 2001 |
Image and video coding › image quality assessment
sharpness metric |
0.0 | 1 | 2001 | Practical Issues in Pixel-Based Autofocusing for Machine Vision · ICRA 2001 |
Computational photography and imaging
focus measure |
0.0 | 1 | 2001 | Practical Issues in Pixel-Based Autofocusing for Machine Vision · ICRA 2001 |
Methods — techniques the papers use, named apart from their topics
sharpness measures · 0.0search algorithm · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2001 | Practical Issues in Pixel-Based Autofocusing for Machine VisionabstractDifferent autofocusing methods exist for many cameras today. While not ignoring commercially available methods requiring specialized hardware, this paper focuses mainly on pixel based autofocusing algorithms as applied to CCD camera systems. Different measures of image sharpness are compared. For each of these, different algorithms for searching the best lens setting are assessed in terms of performance as well as their applicability to various situations. In addition, several other factors potentially affecting camera focusing are also discussed. Based on the information obtained, this research attempts to formulate a robust autofocusing algorithm. Kuang-Chern Ng, Aun Neow Poo, Marcelo H. Ang |
ICRA | 1 |