Comparing SVM with ANN of Aerial Images Segmentation

Comparing SVM with ANN of Aerial Images Segmentation

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Abstract


Comparing SVM with ANN of Aerial Images Segmentation

Fang Xu
School of Geodesy and Geomatics Wuhan University
Wuhan, China

Qin Yan

Abstract
SVM is a new learning machine for two-group classification problems. Artificial Neural Network (ANN) is applications widely near years. This paper uses the two methods to classify and segment aerial images. The same samples and features are used for classify and segment. The results indicate that SVM is better than ANN. The reason is ANN complete depends on the original power value, which don’t have a robust decided method. People could find the best C of SVM in several times based on the experience.