A Lightweight Self-Supervised Representation Learning Framework for Depression Risk Profiling from Synthetic Daily Behavioural Trajectories ...

Apple has introduced a new AI model that can turn a single image into a realistic 3D object with accurate lighting and ...

Abstract: Smartphone-based Human Activity Recognition (HAR) typically relies on deep learning models. However, performance varies with encoder architecture and the availability of labeled data. To ...

Abstract: Non-Intrusive Load Monitoring (NILM) is a promising approach for energy disaggregation, enabling the identification of appliance-specific energy consumption from aggregated electrical ...