iPSD enables self-supervised training of deep EEG denoisers by learning to partition noisy segments into independent noisy realizations of the same neural activity, achieving state-of-the-art performance at very low SNR without clean references.
Automatic identification and removal of ocular artifacts from EEG using wavelet transform.Measurement Science Review, 6(4): 45–57
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Enabling Unsupervised Training of Deep EEG Denoisers With Intelligent Partitioning
iPSD enables self-supervised training of deep EEG denoisers by learning to partition noisy segments into independent noisy realizations of the same neural activity, achieving state-of-the-art performance at very low SNR without clean references.