Translated data: The research team from Daegu University of Science and Technology in South Korea has successfully developed a small sample learning model that can accurately classify brain waves with just a small amount of data. This breakthrough is expected to drive new advancements in brain wave research, overcoming the limitation of traditional deep learning models that require large amounts of data. The team employed various modules to enhance the model's classification accuracy, achieving a cross-individual classification accuracy of up to 76%. This research will have a profound impact on the medical and brain-computer interface fields, paving the way for a better understanding and application of brain wave data.