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One Model for All: Universal Pre-training for EEG based Emotion Recognition across Heterogeneous Datasets and Paradigms

This work proposes 'One Model for All', a universal pre-training framework for EEG analysis across disparate datasets, and paves the way for more universal, scalable, and effective pre-trained models for diverse EEG analysis tasks.

Xiang Li, You Li, Yazhou Zhang · 0 citations

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