The University of Calgary’s Biometric Technologies Laboratory is examining biometrics in conjunction with neural networks to understand whether different biometric measurements can stimulate security systems to improve their recognition process, reports R&D.
Lab head Professor Marina Gavrilova hopes that the lab’s work will improve accuracy and the overall recognition process by simulating the brain and its learning patterns through mathematical algorithms.
The algorithms use multiple biometric measurements, including fingerprint, voice, gait or facial features, to pull together a more complete assessment of who someone is. With more than one source of information, artificial intelligence applications can learn and adapt and train itself to incorporate new and different types of data into its decision making process.
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