The nature of statistical learning theory
The nature of statistical learning theory
An introduction to support Vector Machines: and other kernel-based learning methods
An introduction to support Vector Machines: and other kernel-based learning methods
A Tutorial on Support Vector Machines for Pattern Recognition
Data Mining and Knowledge Discovery
Blobworld: Image Segmentation Using Expectation-Maximization and Its Application to Image Querying
IEEE Transactions on Pattern Analysis and Machine Intelligence
Perfect image segmentation using pulse coupled neural networks
IEEE Transactions on Neural Networks
An introduction to kernel-based learning algorithms
IEEE Transactions on Neural Networks
A comparison of methods for multiclass support vector machines
IEEE Transactions on Neural Networks
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This paper presents an effective and efficient method for solving scenery image segmentation by applying the SVMs methodology. Scenery image segmentation is regarded as a data classification problem, and is effectively answered by the proposed method in this paper. Using the model selection in our system architecture, our system is relatively simple compared to other conventional heuristic image segmentation approaches yet demonstrates promising classification results.