A Bayesian approach for modeling sensor influence on quality, liveness and match score values in fingerprint verification - researchr publication related

researchr

You are not signed in
Sign in
Sign up

Ajita Rattani, Norman Poh, Arun Ross. A Bayesian approach for modeling sensor influence on quality, liveness and match score values in fingerprint verification. In 2013 IEEE International Workshop on Information Forensics and Security, WIFS 2013, Guangzhou, China, November 18-21, 2013. pages 37-42, IEEE, 2013. [doi]

The following publications are possibly variants of this publication:

Bayesian Belief models for integrating match scores with liveness and quality measures in a fingerprint verification systemYaohui Ding, Ajita Rattani, Arun Ross. icb 2016: 1-8 [doi]

Combining match scores with liveness values in a fingerprint verification systemEmanuela Marasco, Yaohui Ding, Arun Ross. btas 2012: 418-425 [doi]

runs on WebDSL