Abstract
As the Internet became popular, the volume of digital multimedia data is exponentially increased in all aspects of our life. This drastic increment in multimedia data causes unwelcome deliveries of adult image contents to the Internet. Consequently, a large number of children are wide-open to these harmful contents. In this paper, we propose an efficient classification system that can categorize the images into multiple classes such as swimming suit, topless, nude, sexual act, and normal. The experiment shows that this system achieved more than 80% of the success rate. Thus, the proposed system can be used as a framework for web contents rating systems.
This paper was supported by the New Faculty Research Fund at Konkuk University in 2004
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Kim, W., Lee, HK., Park, J., Yoon, K. (2005). Multi Class Adult Image Classification Using Neural Networks. In: Kégl, B., Lapalme, G. (eds) Advances in Artificial Intelligence. Canadian AI 2005. Lecture Notes in Computer Science(), vol 3501. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11424918_23
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DOI: https://doi.org/10.1007/11424918_23
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-25864-3
Online ISBN: 978-3-540-31952-8
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