Geodesic
Automatic image classification for content filtering
Informacionnye tehnologii i vyčislitelnye sistemy, no. 3 (2015), pp. 3-12

Voir la notice de l'article provenant de la source Math-Net.Ru

The paper presents a survey of methods for image classification in the context of Web content filtering, as well as results of new experiments using convolutional neural networks and SVM with bag-of-visual-words. Within the experiments, a special difficult dataset was collected that consisting of two hardly distinguishable classes. The quality achieved using convolutional neural network is higher than that of traditional methods in the complicated conditions. Thus, the classifier based on convolutional neural networks proved to be very useful for purposes of Web content filtering.
Keywords: convolutional neural networks, artificial neural networks, bag of visual words, content filtering, dynamic content filtering.
Mots-clés : image classification 
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     title = {Automatic image classification for content filtering},
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     year = {2015},
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V. P. Fralenko; R. E. Suvorov; R. I. Ovcharenko; I. A. Tikhomirov. Automatic image classification for content filtering. Informacionnye tehnologii i vyčislitelnye sistemy, no. 3 (2015), pp. 3-12. http://geodesic.mathdoc.fr/item/ITVS_2015_3_a0/