EDBT 2026 Demo / reviewers in the wild / expert
Rong-Huah Ju
dblp:36/639
· DBLP profile ↗
2ranked-venue papers
1as first author
0since 2021 · last 1994
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 1 · 1 first-authorGraphics, computer vision, multimedia, augmented reality and games · 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.
| Theoretical computer science
1 paper |
Coding theory · 100% | |
| Computer graphics and multimedia
1 paper |
Image and video processing · 100% |
Topics — the 4 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Coding theory › source coding › entropy coding
arithmetic coding |
0.0 | 1 | 1994 | Data compression on multifont Chinese character patterns · IEEE Trans. Image Process. 1994 |
Coding theory
source coding |
0.0 | 1 | 1994 | Data compression on multifont Chinese character patterns · IEEE Trans. Image Process. 1994 |
Coding theory › source coding
source modeling |
0.0 | 1 | 1994 | Data compression on multifont Chinese character patterns · IEEE Trans. Image Process. 1994 |
Image and video processing
document image processing |
0.0 | 1 | 1994 | Data compression on multifont Chinese character patterns · IEEE Trans. Image Process. 1994 |
Methods — techniques the papers use, named apart from their topics
redundancy-gathering algorithm · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 1994 | Data compression on multifont Chinese character patternsabstractThe problems arising in the modeling and coding of digital Chinese character patterns for noiseless compression purposes are discussed. The modeling is intended to capture the maximum redundancies of the source under the consideration of relevant parameters. In this study, a redundancy-gathering algorithm is proposed in which a 2-D parsing tree is used, and the nodes to extend the tree are ranked according to the maximum redundancy gathered. Hence, the modeling represented by the tree can achieve great performance in the small number of nodes. The algorithm is then applied to evaluate the performance of arithmetic coding for digital Chinese character patterns. The results are compared to those of the traditional compression methods. In the same complexity, the authors find that their algorithm can improve the coding efficiency as high as 25.54%, 30.23%, 32.17%, 15.90%, and 27.58%, for five Chinese fonts, respectively. Mu-King Tsay, Chia-Hsu Kuo, Rong-Huah Ju, Ming-Ko Chiu |
IEEE Trans. Image Process. | 3 |
| 1991 | Zooming techniques on digital Chinese character patterns: a further study and improvement
Rong-Huah Ju, I-Chang Jou, Mu-King Tsay |
Image Vis. Comput. | 1 |