Tag: human activity recognition

A new graph neural network framework called GlucoSense combines smartphone activity recognition with glucose forecasting to identify early type 2 ...

Researchers at Durham University have developed a dual-stream neural network that applies parallel attention to sensor modalities and time steps, ...

Researchers in India have developed CAT-Net, a hybrid deep learning model combining convolutional networks, coordinate attention, and Transformer encoders to ...

Researchers at the University of the Punjab have introduced HumCareADL, a demographically diverse multimodal wearable dataset, and HyMCL-Net, a hybrid ...

Researchers have introduced a Riemannian manifold-based loss function that pushes multimodal Transformer models to state-of-the-art accuracy in human activity recognition ...

Researchers at Aston University have created SEdgeNet, a graph neural network that recognises human activities from sparse millimetre-wave radar point ...

Researchers in India have developed a generative adversarial framework that synthesizes realistic radar micro-Doppler spectrograms, lifting human activity recognition accuracy ...

A new study introduces auditable update-utility certificates that verifiably measure the value of each client's contribution in personalized federated learning ...

A new artificial intelligence model that reads time series data the way a skilled human analyst might—by looking at both ...