4 papers
Omni-modal decomposition autoencoders learn full-stack wearable disentangled representations
Ioannis Ziogas, Ensieh Khazaei, Bilal Taha +4
Learning disentangled representations is a key requirement for developing versatile, general-purpose, and sustainable models in multi-modal wearable computing. However, existing ap…
Multimodal Biometric Authentication Using Camera-Based PPG and Fingerprint Fusion
Xue Xian Zheng, M. M. Ur Rahma, Bilal Taha +3
Camera-based photoplethysmography (PPG) obtained from smartphones has shown great promise for personalized healthcare and secure authentication. This paper presents a multimodal bi…
CDFL: Efficient Federated Human Activity Recognition using Contrastive Learning and Deep Clustering
Ensieh Khazaei, Alireza Esmaeilzehi, Bilal Taha +1
In the realm of ubiquitous computing, Human Activity Recognition (HAR) is vital for the automation and intelligent identification of human actions through data from diverse sensors…
Learned 3D Shape Representations Using Fused Geometrically Augmented Images: Application to Facial Expression and Action Unit Detection
Bilal Taha, Munawar Hayat, Stefano Berretti +1
This paper proposes an approach to learn generic multi-modal mesh surface representations using a novel scheme for fusing texture and geometric data. Our approach defines an invers…