We classify 3D aerial LiDAR scattered height data into buildings, trees, roads, and grass using the Support Vector Machine (SVM) algorithm. To do so we use five features: height, ...
Suresh K. Lodha, Edward J. Kreps, David P. Helmbol...
In this paper we propose a modified framework of support vector machines, called Oblique Support Vector Machines(OSVMs), to improve the capability of classification. The principl...
Anomaly detection for network intrusion detection is usually considered an unsupervised task. Prominent techniques, such as one-class support vector machines, learn a hypersphere ...
Support vector machine (SVM) is a new learning method developed in recent years based on the foundations of statistical learning theory. By taking a transductive approach instead ...
In active learning based music retrieval systems, providing multiple samples to the user for feedback is very necessary. In this paper, we present a new multi-samples selection st...