190 citations · 1.4k across the 27 of their papers we have counts for
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Deep Reinforcement Learning Models Predict Visual Responses in the Brain: A Preliminary Result
Maytus Piriyajitakonkij, Sirawaj Itthipuripat, Theerawit Wilaiprasitporn +1
Supervised deep convolutional neural networks (DCNNs) are currently one of the best computational models that can explain how the primate ventral visual stream solves object recogn…
Revealing Preference in Popular Music Through Familiarity and Brain Response
Soravitt Sangnark, Phairot Autthasan, Puntawat Ponglertnapakorn +8
Music preference was reported as a factor, which could elicit innermost music emotion, entailing accurate ground-truth data and music therapy efficiency. This study executes statis…
A Pilot Study on Visually Stimulated Cognitive Tasks for EEG-Based Dementia Recognition
Supavit Kongwudhikunakorn, Suktipol Kiatthaveephong, Kamonwan Thanontip +9
In the status quo, dementia is yet to be cured. Precise diagnosis prior to the onset of the symptoms can prevent the rapid progression of the emerging cognitive impairment. Recent…
MIN2Net: End-to-End Multi-Task Learning for Subject-Independent Motor Imagery EEG Classification
Phairot Autthasan, Rattanaphon Chaisaen, Thapanun Sudhawiyangkul +7
Advances in the motor imagery (MI)-based brain-computer interfaces (BCIs) allow control of several applications by decoding neurophysiological phenomena, which are usually recorded…