Demo Data from EDBT 2026 / reviewers in the wild / expert
Chung Ta King
dblp:61/3954
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 1995
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Graphics, 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.
| Computer architecture, parallel and distributed computing, and storage systems
1 paper |
Hardware accelerators and domain-specific architectures · 50% Parallel and multicore computing · 50% | |
| 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 |
|---|---|---|---|---|
Parallel and multicore computing › parallel algorithms
parallel image processing |
0.0 | 1 | 1995 | Pipeline architectures for recursive morphological operations · IEEE Trans. Image Process. 1995 |
Hardware accelerators and domain-specific architectures
systolic array |
0.0 | 1 | 1995 | Pipeline architectures for recursive morphological operations · IEEE Trans. Image Process. 1995 |
Image and video processing
mathematical morphology |
0.0 | 1 | 1995 | Pipeline architectures for recursive morphological operations · IEEE Trans. Image Process. 1995 |
Methods — techniques the papers use, named apart from their topics
pipeline architecture · 0.0distributed-memory multicomputer · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 1995 | Pipeline architectures for recursive morphological operationsabstractIntroduces efficient pipeline architectures for the recursive morphological operations. The standard morphological operation is applied directly on the original input image and produces an output image. The order of image scanning in which the operator is applied to the input pixels is irrelevant. However, the intent of the recursive morphological operations is to feed back the output at the current scanning pixel to overwrite its corresponding input pixel to be considered into computation at the following scanning pixels. The resultant output image by recursive morphology inherently depends on the image scanning sequence. Two pipelined implementations of the recursive morphological operations are presented. The design of an application-specific systolic array is first introduced. The systolic array uses 3 n cells to process an nxn image in 6 n-2 cycles. The cell utilization rate is 100%. Second, a parallel program implementing the recursive morphological operations and running on distributed-memory multicomputers is described. Performance of the program can be finely tuned by choosing appropriate partition parameters. Frank Y. Shih, Chung Ta King, Christopher C. Pu |
IEEE Trans. Image Process. | 2 |