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Neural Network Based Adult Image Classification

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 3696))

Abstract

Digital multimedia data is dramatically being increased everyday since the Internet became popular. This increment in multimedia data increases adult image contents to the Internet as well. Consequently, a large number of children are exposed to these X-rated contents. In this paper, we propose an efficient classification system that can categorize input images into adult or non-adult images. The simulation shows that this system achieved 95% of the true rate whereas it reduces the false positive rate below 3%.

This paper was supported by Electronics and Telecommunications Research Institute (Project No. 0801-2004-0025).

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© 2005 Springer-Verlag Berlin Heidelberg

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Kim, W., Lee, HK., Yoo, S.J., Baik, S.W. (2005). Neural Network Based Adult Image Classification. In: Duch, W., Kacprzyk, J., Oja, E., Zadrożny, S. (eds) Artificial Neural Networks: Biological Inspirations – ICANN 2005. ICANN 2005. Lecture Notes in Computer Science, vol 3696. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11550822_75

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  • DOI: https://doi.org/10.1007/11550822_75

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-28752-0

  • Online ISBN: 978-3-540-28754-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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