Abstract: Accurately detecting human attention levels is a key challenge in cognitive neuroscience, with broad application value in improving productivity. Although Electroencephalography (EEG) ...
Abstract: Deep learning models often emphasize structural information over long-range dependencies when producing cleaner images. To enhance the robustness of the resulting denoisers, this work ...
Abstract: Convolutional Neural Networks (CNNs) are extensively utilized for image classification due to their ability to exploit data correlations effectively. However, traditional CNNs encounter ...