FEW-SHOT CLASSIFICATION OF EEG WITH QUASI-INDUCTIVE TRANSFER LEARNING
Brain-computer interfaces (BCIs) are devices that enable people with disabilities to use their thoughts to control external devices and restore or improve their bodily functions. One important aspect of BCIs is the classification of electroencephalography (EEG) signals, which measure brain activity and can be difficult to interpret. To address this challenge, we use time-frequency transformations