VLDB 2026 Research / reviewers in the wild / expert
James I. Gimlett
dblp:272/4816
· DBLP profile ↗
1ranked-venue papers
1as first author
0since 2021 · last 1975
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Computer networks · 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 coding · 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 coding › transform coding
adaptive transform coding |
0.0 | 1 | 1975 | Use of "Activity" Classes in Adaptive Transform Image Coding · IEEE Trans. Commun. 1975 |
Image and video coding › rate control
bit allocation |
0.0 | 1 | 1975 | Use of "Activity" Classes in Adaptive Transform Image Coding · IEEE Trans. Commun. 1975 |
Image and video coding
transform coding |
0.0 | 1 | 1975 | Use of "Activity" Classes in Adaptive Transform Image Coding · IEEE Trans. Commun. 1975 |
Methods — techniques the papers use, named apart from their topics
truncation and quantization rules · 0.0activity index · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 1975 | Use of "Activity" Classes in Adaptive Transform Image CodingabstractThe weighted sum of the absolute values of the transform coefficients, defined herein as the activity index, is proposed as an objective measure of scene busyness (i.e., the density of significant scene detail). For an image divided into subpictures, it is possible to classify each subpicture into a finite number (say four) of categories according to its computed activity index. A different coding scheme, involving different truncation and quantization rules and hence a different number of bits, is used for each activity category. Data compression is efficiently achieved by assigning more bits to code those portions of the image showing the most detail. James I. Gimlett |
IEEE Trans. Commun. | 1 |