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Found 5 papers, 4 papers with code
Temporal Action Localization for Inertial-based Human Activity Recognition
Our results show that state-of-the-art TAL models are able to outperform popular inertial models on 4 out of 6 wearable activity recognition benchmark datasets, with improvements ranging as much as 25% in F1-score.
Hang-Time HAR: A Benchmark Dataset for Basketball Activity Recognition using Wrist-Worn Inertial Sensors
We present a benchmark dataset for evaluating physical human activity recognition methods from wrist-worn sensors, for the specific setting of basketball training, drills, and games.
WEAR: An Outdoor Sports Dataset for Wearable and Egocentric Activity Recognition
Though research has shown the complementarity of camera- and inertial-based data, datasets which offer both egocentric video and inertial-based sensor data remain scarce.
Egocentric Activity Recognition
Human Activity Recognition
+2
Tutorial on Deep Learning for Human Activity Recognition
Activity recognition systems that are capable of estimating human activities from wearable inertial sensors have come a long way in the past decades.
Improving Deep Learning for HAR with shallow LSTMs
Recent studies in Human Activity Recognition (HAR) have shown that Deep Learning methods are able to outperform classical Machine Learning algorithms.
