Demonstration venue · read-only. Every page can be browsed; the buttons that would change it are switched off. Create an account to run TaxoReview on your own data. A simulation from public publication records: the people listed were not invited and did not agree to review.
? Tutorial for this page
Demo Data from EDBT 2026 / reviewers in the wild / expert

Rajev Khanna

dblp:317/5278 · DBLP profile ↗
← Back
2ranked-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 · 2

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

TopicWeightPapersLastEvidence papers
Biometric security
biometric performance evaluation		 0.011997
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
YearPublicationVenuePosition
1997 Prolog to: Biometrics: Privacy's Foe Or Privacy's Friend?
Weicheng Shen, Rajev Khanna, John D. Woodward
 Proc. IEEE2
1997 Evaluation of automated biometrics-based identification and verification systems
abstract
Recent 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. IEEE3