Demo Data from EDBT 2026 / reviewers in the wild / expert
Marc Surette
dblp:317/5215
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 1997
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Applied, interdisciplinary, general and emerging computing · 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.
| Network and information security
1 paper |
Biometric security · 100% |
Topics — the 1 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Biometric security
biometric performance evaluation |
0.0 | 1 | 1997 | Evaluation of automated biometrics-based identification and verification systems · Proc. IEEE 1997 |
Methods — techniques the papers use, named apart from their topics
statistical analysis · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 1997 | Evaluation of automated biometrics-based identification and verification systemsabstractRecent advancements in computer technology have increased the use of automated biometric-based identification and verification systems. These systems are designed to detect the identity of an individual when it is unknown or to verify the individual's identity when it is provided. These systems typically contain a series of complex technologies that work together to provide the desired results in turn, evaluating these systems is also a complex process. The authors provide a method that may be used to evaluate the performance of automated biometric-based systems. The method is derived from fundamental statistics and is applicable to a variety of systems. Examples are provided to demonstrate the practicality of the method. Weicheng Shen, Marc Surette, Rajev Khanna |
Proc. IEEE | 2 |