4 accepted papers
Human action recognition in dark videos is a challenging task for computer vision due to the low quality of the videos filmed in the dark. Recent studies focused on applying dark enhancement methods to improve the visibility of the video. However, such video processing results in the loss of critica
Motor Imagery (MI) is essential in the Brain-Computer Interface (BCI). Given the multi-source nature of EEG instability across subjects/sessions and the privacy concerns when dealing with data from other institutions, the importance of multi-source-free domain adaptation (MSFDA) becomes evident in c…
Electrocardiography (ECG) is a widely used cardiac measurement for detecting cardiovascular conditions, while self-supervised learning leverages unlabeled data for model pre-training. However, current self-supervised frameworks for ECG signals generally lack a comprehensive understanding of intra-he…
The non-invasive and easily accessible characteristics of electrocardiogram (ECG) attract many studies targeting AI-enabled cardiovascular-related disease screening tools based on ECG. However, the high cost of manual labels makes high-performance deep learning models challenging to obtain. Hence, w…