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: Applying Support Vector Machine (SVM) theory to hyperspectral images classification can significantly mitigate the decline in classification performance caused by the curse of dimensionality ...

Abstract: Deep Neural Networks (DNNs) have demonstrated remarkable effectiveness in remote sensing (RS) image processing. However, they remain vulnerable to adversarial examples, which are generated ...