Training Support Vector Machines: an Application to Face Detection
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
One-class support vector machines-an application in machine fault detection and classification
Computers and Industrial Engineering
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The problem of abandoned land from mining activities is aggravated since the coal boom. Activities of excavating coal exscind natural vegetation and deposit stone on the natural land that modified the natural land contribute to waste farmlands. This paper presents the comparableness of SVMs method to artificial neural networks in the outlier detection problem of high dimensions. Experiments performed on real dataset show that the performance of this method is mostly superior to that of artificial neural networks. The proposed method, SVMs served to exemplify that kernel-based learning algorithms can be employed as an efficient method for evaluating the revegetation potentiality of abandoned lands from coal mining activities