A lightweight one-block transformer architecture for EEG-based cognitive workload classification that uses under 0.5 million parameters and 0.02 GFLOPs.
A full transformer-based framework for automatic pain estimation using videos
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Lightweight transformer fuses raw and spectral fNIRS representations via unified tokenization for competitive pain recognition on the AI4Pain dataset while remaining computationally compact.
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One-Block Transformer (1BT) for EEG-Based Cognitive Workload Assessment
A lightweight one-block transformer architecture for EEG-based cognitive workload classification that uses under 0.5 million parameters and 0.02 GFLOPs.
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A Lightweight Transformer for Pain Recognition from Brain Activity
Lightweight transformer fuses raw and spectral fNIRS representations via unified tokenization for competitive pain recognition on the AI4Pain dataset while remaining computationally compact.