Compact feature selection improves wearable activity transfer across datasets
A study combining source relevance with unlabeled cross-dataset stability selected 48 wearable-signal features and improved MHEALTH-to-PAMAP2 activity classification.
A study combining source relevance with unlabeled cross-dataset stability selected 48 wearable-signal features and improved MHEALTH-to-PAMAP2 activity classification.
Researchers have developed xAutoGA, an open-source automated deep learning platform that uses a genetic algorithm, natural-selection visualizations, rule extraction, and ...
Researchers have developed a personalized N-of-1 transformer framework that learns an individual's daily behavior patterns from smart home activity logs ...
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© 2025 Scienmag - Science Magazine