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We propose an image aesthetic quality assessment algorithm, which considers personal taste in addition to generally perceived preference. This problem is formulated by a combination of two different learning frameworks based on support vector machines—Support Vector Regression (SVR) and Ranking SVM (R-SVM), where SVR learns a general model based on public datasets and R-SVM adjusts the model to accommodate...
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