We propose DynaGuide, a generalizable dynamic guidance framework that enables zero-shot guided unsupervised semantic segmentation without requiring labeled training data. The …
We propose an enhanced unsupervised domain adaptation framework for EEG-based emotion recognition that achieves robust cross-dataset generalization without requiring target-domain …
We present an unsupervised domain adaptation approach for ECG arrhythmia classification that generalizes across different databases and lead configurations without requiring …
We propose a multilevel stress assessment framework that fuses ECG signals with contextual data from a virtual reality environment. The system classifies multiple levels of …
We propose the Focal Tversky Loss, a generalized loss function that addresses extreme class imbalance in medical image segmentation. Combined with an improved Attention U-Net …