首页|School of Mathematics Researchers Update Knowledge of Intelligence Technology (Feature extraction and learning approaches for cancellable biometrics: A survey)
School of Mathematics Researchers Update Knowledge of Intelligence Technology (Feature extraction and learning approaches for cancellable biometrics: A survey)
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NETL
NSTL
Wiley
Investigators discuss new findings in intelligence technology. According to news re-porting from the School of Mathematics by NewsRx journalists, research stated, "Biometric recognition is a widely used technology for user authentication." Funders for this research include Australian Research Council. Our news correspondents obtained a quote from the research from School of Mathematics: "In the application of this technology, biometric security and recognition accuracy are two important issues that should be considered. In terms of biometric security, cancellable biometrics is an effective technique for protecting biometric data. Regarding recognition accuracy, feature representation plays a significant role in the performance and reliability of cancellable biometric systems. How to design good feature representations for cancellable biometrics is a challenging topic that has attracted a great deal of attention from the computer vision community, especially from researchers of cancellable biometrics. Feature extraction and learning in cancellable biometrics is to find suitable feature representations with a view to achieving satisfactory recognition performance, while the privacy of biometric data is protected."
School of MathematicsIntelligence TechnologyMachine LearningTechnology
NETL
NSTL
Wiley
