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tinyML Asia 2021 An approach to dynamically integrate heterogenous AI components in a multimodal user authentication system use case Haochen XIE 謝 昊辰; ｺﾄｲ ｺｳｼﾝ, Project Leader, Team Dragon, AnchorZ Inc. n this talk, we will introduce our approach to a challenging task: to effectively and dynamically integrate multiple AI-backed components where each component varies in the kind of AI technologies it uses, in order to implement a single functionality — continuous multimodal user authentication. In building our next-generation user authentication system — DZ Security —, we needed a way to effectively integrate multiple elemental authentication methods, such as facial recognization, voice recognization, touch pattern, etc., that employ very different types of AI technologies, such as DNN, RNN, analytical regression, etc., in a flexible and effective manner. We also needed the combination method to support an open set of element
