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.

This is an accepted paper at the 10th International Conference on Machine Learning and Computing (ICMLC) in Macau, China on February 26-28, 2018. The full paper on this project may be read at ...

Abstract: SVM may have great difficulty in its realization, even can not work properly because of the tremendous increase of compute time and memory for large-scale training set. A new fast learning ...

Abstract: Support vector machines (SVM) are attractive for the classification of remotely sensed data with some claims that the method is insensitive to the dimensionality of the data and, therefore, ...

Binary classification algorithms are essential for achieving high accuracy in modelling. Support Vector Machines are popular among data scientists for binary classification tasks. One-vs-Rest and ...

A binary classifier implemented with a support vector machine (SVM) written in C++ and converted to HLSL to be used inside VRChat. I have included a program that allows you to train your own detector.

As a data-driven dimensionality reduction and visualization tool, t-distributed stochastic neighborhood embedding (t-SNE) has been successfully applied to a variety of fields. In recent years, it has ...

Robot-assisted rehabilitation is a growing field that can provide an intensity, quality, and quantity of treatment that exceed therapist-mediated rehabilitation. Several control algorithms have been ...