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Neural Network Based Adult Image Classification

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Artificial Neural Networks: Biological Inspirations – ICANN 2005 (ICANN 2005)

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

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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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