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Found 5 papers, 1 papers with code
Stress Detection using Context-Aware Sensor Fusion from Wearable Devices
SELF-CARE uses a learning-based classifier to process sensor features and model the environmental variations in sensing conditions known as the noise context.
SELF-CARE: Selective Fusion with Context-Aware Low-Power Edge Computing for Stress Detection
Detecting human stress levels and emotional states with physiological body-worn sensors is a complex task, but one with many health-related benefits.
EcoFusion: Energy-Aware Adaptive Sensor Fusion for Efficient Autonomous Vehicle Perception
Autonomous vehicles use multiple sensors, large deep-learning models, and powerful hardware platforms to perceive the environment and navigate safely.
HydraFusion: Context-Aware Selective Sensor Fusion for Robust and Efficient Autonomous Vehicle Perception
To address these limitations, we propose HydraFusion: a selective sensor fusion framework that learns to identify the current driving context and fuses the best combination of sensors to maximize robustness without compromising efficiency.
Graph Learning for Cognitive Digital Twins in Manufacturing Systems
In this paper, we detail the cognitive digital twin as the next stage of advancement of a digital twin that will help realize the vision of Industry 4. 0.
