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In this paper, we propose an innovative classification method which combines texture features of images filtered by Gaussian derivative models with extreme learning machine (ELM). In the texture image classification, feature extraction is a very crucial step. Thusly, we use linear filters consisting of two Gaussian derivative models, difference of Gaussian (DOG) and difference of offset Gaussian (DOOG),...
In this paper, we propose a fast manifold learning strategy to estimate the underlying geometrical distribution and develop the relevant mathematical criterion on the basis of the extreme learning machine (ELM) in the high-dimensional space. The local tangent space alignment (LTSA) method has been used to perform the manifold production and the single hidden layer feedforward network (SLFN) is established...
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