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- W1578350075 abstract "A novel semi-supervised support vector machine (S/sup 3/VM) algorithm is developed for segmentation of texture images. The method classifies the uniform-texture regions from the regions of boundaries. The various-order statistics of the textures within a two-dimensional sliding window are measured. A K-means algorithm is used to label the two clusters approximately in the overall image. However, only those clusters which are very close to the class centres are labelled. Therefore, at this stage we have both the training and the working sets. A non-linear S/sup 3/VM is then developed to exploit both sets to classify the regions. It is demonstrated that the algorithm is robust and the misclassification error is negligible. However, there may be a minor misplacement of the edges." @default.
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- W1578350075 date "2005-04-19" @default.
- W1578350075 modified "2023-09-23" @default.
- W1578350075 title "A semi-supervised support vector machine for texture segmentation" @default.
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- W1578350075 doi "https://doi.org/10.1109/icip.2004.1418730" @default.
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