Support Vector Machines have received considerable attention from the pattern recognition community in recent years. They have been applied to various classical recognition problems achieving comparable or even superior results to classifiers such as neural networks. We investigate the application of Support Vector Machines (SVMs) to the problem of road recognition from remotely sensed images using edge-based features. We present very encouraging results from our experiments, which are comparable to decision tree and neural network classifiers. © Springer-Verlag Berlin Heidelberg 2005.
CITATION STYLE
Lai, J. Y., Sowmya, A., & Trinder, J. (2005). Support vector machine experiments for road recognition in high resolution images. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3587 LNAI, pp. 426–436). Springer Verlag. https://doi.org/10.1007/11510888_42
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