Nota had a paper accepted for the CIKM 2019 International Workshop on Data and Text Mining in Biomedicine, to be held November in Beijing, China. The CIKM, International Conference on Information and Knowledge Management, is a top-tier ACM conference in the areas of information retrieval, knowledge management, and databases. The purpose of the conference is to identify challenging problems facing the development of future knowledge and information systems and to shape future directions of research by soliciting and reviewing high quality, applied and theoretical research findings.(kmeducation.com) Nota will be presenting a paper titled Deep User Identification Model with Multiple Biometrics at the conference.
Date of acceptance: 2019. 08. 23.
Abstract: Identification using biometrics is an important yet challenging task. Abundant research has been conducted on identifying personal identity or gender using given signals. Various types of biometrics such as electrocardiogram (ECG), electroencephalogram (EEG), face, fingerprint, and voice have been used for these tasks. Most research has only focused on single modality or a single task, while the combination of input modality or tasks is yet to be investigated. In this paper, we propose deep identification and gender classification using multimodal biometrics. Our model uses ECG, fingerprint, and facial data. It then performs two tasks: gender identification and classification. By engaging multi-modality, a single model can handle various input domains without training each modality independently, and the correlation between domains can increase its generalization performance on the tasks.