Tag: temporal attention

Researchers developed a confidence-gated convolutional neural network and bidirectional recurrent model that enhances rare arrhythmia classification on electrocardiogram signals while ...

A hierarchical attention model reported 0.913 detection accuracy, 83.6% zero-shot attack recognition and 29.8-millisecond average detection latency in computational experiments.

A weather-aware recurrent neural network delivered more accurate extreme-condition electricity-load forecasts while using an 8.1 MB edge footprint and 9.2-millisecond ...

A hybrid attention model combined six years of field observations with orchard geography to forecast occurrence levels and intensity for ...

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

A new graph neural network framework called AlloPool distills molecular dynamics simulations into minimal, time-resolved interaction networks that reveal how ...

A new prediction-based neural network called RMTA-Net combines recurrent temporal processing, learnable memory banks, and adaptive attention to detect video ...

Researchers in India have developed a graph neural network framework called TADGLN-LSTM that quantifies how individual scientists' research topics drift ...