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    The MLPBOON Predicting Media Interestingness System for MediaEval 2016

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    ABSTRACT This paper describes the system developed by team MLP-BOON for MediaEval 2016 Predicting Media Interestingness Image Subtask. After experimenting with various features and classifiers on the development dataset, our final system involves use of CNN features (fc7 layer of AlexNet) for the input representation and logistic regression as the classifier. For the proposed method, the MAP for the best run reaches a value of 0.229
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