4 accepted papers
Emotion recognition from physiological signals has substantial potential for applications in mental health and emotion-aware systems. However, the lack of standardized, large-scale evaluations across heterogeneous datasets limits progress and model generalization. We introduce FEEL (Framework for Em…
EEVR (Emotion Elicitation in Virtual Reality) is a novel dataset specifically designed for language supervision-based pre-training of emotion recognition tasks, such as valence and arousal classification. It features high-quality physiological signals, including electrodermal activity (EDA) and phot…
COVID-19 pandemic spreaded across the world in early 2020. It forced many countries to impose lockdown to pre-vent surge in the number of infected cases. There has been a huge impact on social and economic activities worldwide. In this work, we carry out the functional modeling of COVID-19 infection…
Appliance fault in buildings resulting in abnormal energy consumption is known as an anomaly. Traditionally, anomaly detection is performed either at aggregate, i.e., meter-level, or at appliance level. Meter-level anomaly detection does not identify the anomaly-causing appliance, while appliance-le…