Search Results for author:
Found 2 papers, 2 papers with code
Auto deep learning for bioacoustic signals
This study investigates the potential of automated deep learning to enhance the accuracy and efficiency of multi-class classification of bird vocalizations, compared against traditional manually-designed deep learning models.
EEG Synthetic Data Generation Using Probabilistic Diffusion Models
Electroencephalography (EEG) plays a significant role in the Brain Computer Interface (BCI) domain, due to its non-invasive nature, low cost, and ease of use, making it a highly desirable option for widespread adoption by the general public.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
