A new study developed a snore-source classification model that uses STFT spectrograms, pretrained CNN features, and an L2-regularized SVM to identify where snoring originates in the upper airway.
Abstract: Speaker identification in challenging acoustic environments, influenced by noise, reverberation, and emotional fluctuations, requires improved feature extraction techniques. Although ...
Abstract: Non-ferrous copper prices exhibit high noise, non-smoothness, and non-linearity, which pose significant challenges to accurate price prediction. One of the current methods for predicting ...
AI in Precision Psychiatry and Neurodevelopmental Disorders: From Subjective Diagnosis to Objective Biomarkers ...
To ensure robust feature learning from the peaks, a convolution-based peak enhancement (CPE) method has been employed in this work. For feature extraction, the refined signals are processed using two ...
The project automatically fetches the latest papers from arXiv based on keywords. The subheadings in the README file represent the search keywords. Only the most recent articles for each keyword are ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results