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Found 8 papers, 2 papers with code
Temporally Multi-Scale Sparse Self-Attention for Physical Activity Data Imputation
Wearable sensors enable health researchers to continuously collect data pertaining to the physiological state of individuals in real-world settings.
Flexible Beamforming in B5G for Improving Tethered UAV Coverage over Smart Environments
Furthermore, the beamforming gain is mainly concentrated in the target to improve the coverage area based on various scenarios.
A Novel end-to-end Framework for Occluded Pixel Reconstruction with Spatio-temporal Features for Improved Person Re-identification
Person re-identification is vital for monitoring and tracking crowd movement to enhance public security.
PulseImpute: A Novel Benchmark Task for Pulsative Physiological Signal Imputation
The promise of Mobile Health (mHealth) is the ability to use wearable sensors to monitor participant physiology at high frequencies during daily life to enable temporally-precise health interventions.
Transformers for prompt-level EMA non-response prediction
The transformer model achieves a non-response prediction AUC of 0. 77 and is significantly better than classical ML and LSTM-based deep learning models.
Efficient Reservoir Computing using Field Programmable Gate Array and Electro-optic Modulation
The second is the Santa Fe laser data prediction, where a normalized mean square error (NMSE) of 6. 73x10-3 is demonstrated.
Latent Factor Modeling of Users Subjective Perception for Stereoscopic 3D Video Recommendation
In this paper, we introduce a novel recommendation system for stereoscopic 3D movies based on a latent factor model that meticulously analyse the viewer's subjective ratings and influence of 3D video distortions on their preferences.
Learning Shallow Detection Cascades for Wearable Sensor-Based Mobile Health Applications
The field of mobile health aims to leverage recent advances in wearable on-body sensing technology and smart phone computing capabilities to develop systems that can monitor health states and deliver just-in-time adaptive interventions.
