TCN

A comparative study of temporal deep learning architectures for physiological emotion recognition found the Transformer achieved the highest multimodal accuracy on the WESAD dataset at 99.02% +/- 0.51…

An open-source hybrid local framework, RobinHood, combines TCN, LSTM, and Attention deep learning with Captum Integrated Gradients feature attribution to generate deterministic numerical weights for t…

A new neuro-agentic control framework coupling an LLM-based planner with a pre-trained Time-Series Foundation Model (TimesFM) achieved zero physically invalid actions and prevented 33.3% of security b…

Researchers achieved 98.91% accuracy in multimodal emotion recognition from physiological signals by combining LSTM, TCN, and Transformer models with late-fusion ensemble on the WESAD dataset. Transfo…