We introduce a computational design for pattern detection based on a tree-structured network of support vector machines (SVMs). An SVM is associated with each cell in a recursive ...
This paper investigates the use of a one-class support vector machine algorithm to detect the onset of system anomalies, and trend output classification probabilities, as a way to ...
The standard SVM formulation for binary classification is based on the Hinge loss function, where errors are considered not correlated. Due to this, local information in the featu...
Microcalcification (MC) clusters in mammograms can be an indicator of breast cancer. In this work we propose for the first time the use of support vector machine (SVM) learning fo...
Issam El-Naqa, Yongyi Yang, Miles N. Wernick, Niko...
The classification of Electrocardiogram (ECG) is critical for diagnosis and treatment of patients with heart disorders. We present a technique for automatic the detection and clas...