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Titlebook: Artificial Intelligence and Neural Networks; 14th Turkish Symposi F. Acar Savac? Conference proceedings 2006 Springer-Verlag Berlin Heidelb

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Protein Solvent Accessibility Prediction Using Support Vector Machines and Sequence Conservations,ge classifies each residue in a protein sequence as exposed or buried using support vector machine (SVM). The features used in the SVM are physico-chemical properties of the amino acid to be predicted as well as the information coming from its neighboring residues. The SVM-based predictions are refi
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Unsupervised Image Segmentation Using Markov Random Fields,thm to estimate the distribution of the input image and the number of the components is automatically determined by the . (MML) algorithm. Then the segmentation is done by the Iterated Conditional Modes (ICM) algorithm. For testing the segmentation performance, we use both artificial images and real
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https://doi.org/10.1007/978-3-8349-8349-7to calculate the depth of general objects using only two images, one of them being a focused image and the other one a blurred image. Having computed the power spectra of each image, they are divided to obtain a result which is independent from the image content. The result is then used for training
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