Personalized biometric anti-spoofing protection using machine learning and enrollment data
Номер патента: EP4320606A1
Опубликовано: 14-02-2024
Автор(ы): Bence MAJOR, Daniel Hendricus Franciscus DIJKMAN, Davide BELLI, Fatih Murat PORIKLI
Принадлежит: Qualcomm Inc
Опубликовано: 14-02-2024
Автор(ы): Bence MAJOR, Daniel Hendricus Franciscus DIJKMAN, Davide BELLI, Fatih Murat PORIKLI
Принадлежит: Qualcomm Inc
Реферат: Certain aspects of the present disclosure provide techniques and apparatus for biometric authentication using neural-network-based anti-spoofing protection mechanisms. An example method generally includes receiving an image of a biometric data source for a user; extracting, through a first artificial neural network, features for at least the received image; combining the extracted features for the at least the received image and a combined feature representation of a plurality of enrollment biometric data source images; determining, using the combined extracted features for the at least the received image and the combined feature representation as input into a second artificial neural network, whether the received image of the biometric data source for the user is from a real biometric data source or a copy of the real biometric data source; and taking one or more actions to allow or deny the user access to a protected resource based on the determination.
Method and system for operating multiple web pages with anti-spoofing protection
Номер патента: US09607093B2. Автор: Stephen Mark Yolleck,David Anton Walters. Владелец: Microsoft Technology Licensing LLC. Дата публикации: 2017-03-28.