Demo Data from SIGIR 2026 / reviewers in the wild / expert
Stephan R. Veltman
dblp:94/5065
· DBLP profile ↗
1ranked-venue papers
1as first author
0since 2021 · last 1994
—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 1 heaviest of 1, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Image and video processing › document image analysis › character recognition
handwritten character recognition |
0.0 | 1 | 1994 | Hidden Markov models applied to on-line handwritten isolated character recognition · IEEE Trans. Image Process. 1994 |
Methods — techniques the papers use, named apart from their topics
hidden markov model · 0.0baum-welch optimization · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 1994 | Hidden Markov models applied to on-line handwritten isolated character recognitionabstractHidden Markov models are used to model the generation of handwritten, isolated characters. Models are trained on examples using the Baum-Welch optimization routine. Then, given the models for the alphabet, unknown characters can be classified using maximum-likelihood classification. Experiments have been conducted, and an average error rate of 6.9% was achieved over the alphabet consisting of the lowercase English alphabet. Stephan R. Veltman, Ramjee Prasad |
IEEE Trans. Image Process. | 1 |