Demo Data from EDBT 2026 / reviewers in the wild / expert
Jin-Kee Chae
dblp:168/7837
· DBLP profile ↗
1ranked-venue papers
1as first author
0since 2021 · last 2015
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Graphics, computer vision, multimedia, augmented reality and games · 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 |
Image and video processing · 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 › video frame interpolation › interpolation › image interpolation
cubic convolution interpolation |
0.2 | 1 | 2015 | Cubic Convolution Scaler Optimized for Local Property of Image Data · IEEE Trans. Image Process. 2015 |
Image and video processing › video frame interpolation › interpolation
image interpolation |
0.2 | 1 | 2015 | Cubic Convolution Scaler Optimized for Local Property of Image Data · IEEE Trans. Image Process. 2015 |
Image and video processing › image resampling
image rescaling |
0.2 | 1 | 2015 | Cubic Convolution Scaler Optimized for Local Property of Image Data · IEEE Trans. Image Process. 2015 |
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2015 | Cubic Convolution Scaler Optimized for Local Property of Image DataabstractA scaler is one of the most important modules in various video applications, such as ultra-high definition TV and scalable video systems. A variety of scaling techniques have been used to increase the video quality when the resolution of the source image has to be up- and down-scaled. Some conventional schemes exploit the property of local block data. Others consider the edge information of the data to be scaled. In this paper, we formulate a scaling problem to minimize the information loss resulting from the resizing process. The loss is considered in both the spatial and the frequency domains, and then it is minimized to optimize the kernel of the scaler. The simulation results show that the proposed algorithm reduces the information loss more than conventional schemes. When compared with the conventional algorithms, the proposed method outperforms those with similar complexity. Jin-Kee Chae, Jae-Yung Lee, Min-Ho Lee, Jong-Ki Han, Truong Q. Nguyen, Woon-Young Yeo |
IEEE Trans. Image Process. | 1 |