Abstract
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.
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Lai, J.Y., Sowmya, A., Trinder, J. (2005). Support Vector Machine Experiments for Road Recognition in High Resolution Images. In: Perner, P., Imiya, A. (eds) Machine Learning and Data Mining in Pattern Recognition. MLDM 2005. Lecture Notes in Computer Science(), vol 3587. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11510888_42
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DOI: https://doi.org/10.1007/11510888_42
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-26923-6
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