In this work we present InFeRno, an intelligent web pornography elimination system, classifying web pages based solely on their visual content. The main characteristics of our system include: (i) a powerful vector space with a small but sufficient number of features that manage to improve the discriminative ability of the SVM classifier; (ii) an extra class (bikini) that strengthens the performance of the classifier; (iii) an overall classification scheme that achieves high accuracy at considerably lower runtime costs compared to current state-of-the-art systems; and (iv) a full-fledged implementation of the proposed system capable of being integrated with ICAP-aware web proxy cache servers. © 2011 Springer-Verlag.
CITATION STYLE
Karavarsamis, S., Ntarmos, N., & Blekas, K. (2011). InFeRno - An intelligent framework for recognizing pornographic web pages. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6913 LNAI, pp. 638–641). https://doi.org/10.1007/978-3-642-23808-6_46
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