2 papers
cs.LG2026
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…
cs.LG2024
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…