Demo Data from VLDB 2026 / reviewers in the wild / expert
Ryan Connaughton
dblp:09/6291
· DBLP profile ↗
1ranked-venue papers
1as first author
0since 2021 · last 2012
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Security and privacy · 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.
| Network and information security
1 paper |
Biometric security · 100% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Biometric security › iris recognition
cross-sensor matching |
0.1 | 1 | 2012 | A Multialgorithm Analysis of Three Iris Biometric Sensors · IEEE Trans. Inf. Forensics Secur. 2012 |
Biometric security
iris recognition |
0.1 | 1 | 2012 | A Multialgorithm Analysis of Three Iris Biometric Sensors · IEEE Trans. Inf. Forensics Secur. 2012 |
Biometric security › iris recognition
iris matching |
0.0 | 1 | 2012 | A Multialgorithm Analysis of Three Iris Biometric Sensors · IEEE Trans. Inf. Forensics Secur. 2012 |
Methods — techniques the papers use, named apart from their topics
multialgorithm comparison · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2012 | A Multialgorithm Analysis of Three Iris Biometric SensorsabstractThe issue of interoperability between iris sensors is an important topic in large-scale and long-term applications of iris biometric systems. This work compares three commercially available iris sensors and three iris matching systems and investigates the impact of cross-sensor matching on system performance in comparison to single-sensor performance. Several factors which may impact single-sensor and cross-sensor performance are analyzed, including changes in the acquisition environment and differences in dilation ratio between iris images. The sensors are evaluated using three different iris matching algorithms, and conclusions are drawn regarding the interaction between the sensors and the matching algorithm in both the cross-sensor and single-sensor scenarios. Finally, the relative performances of the three sensors are compared. Ryan Connaughton, Amanda Sgroi, Kevin W. Bowyer, Patrick J. Flynn |
IEEE Trans. Inf. Forensics Secur. | 1 |