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Found 4 papers, 1 papers with code
Foundation Models for Structural Health Monitoring
For AD, we achieve a near-perfect 99. 9% accuracy with a monitoring time span of just 15 windows.
Trimming Feature Extraction and Inference for MCU-based Edge NILM: a Systematic Approach
State-of-the-Art approaches are based on Machine Learning methods and exploit the fusion of time- and frequency-domain features from current and voltage sensors.
Source Code Classification for Energy Efficiency in Parallel Ultra Low-Power Microcontrollers
The analysis of source code through machine learning techniques is an increasingly explored research topic aiming at increasing smartness in the software toolchain to exploit modern architectures in the best possible way.
Learning Behavioral Representations of Human Mobility
In this paper, we investigate the suitability of state-of-the-art representation learning methods to the analysis of behavioral similarity of moving individuals, based on CDR trajectories.
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