Multi class adult image classification using neural networks

Authors:
Wonil Kim;Han-Ku Lee;Jinman Park;Kyoungro Yoon
Affiliations:
College of Electronics and Information Engineering at Sejong University, Seoul, Korea;School of Internet and Multimedia Engineering at Konkuk University, Seoul, Korea;College of Electronics and Information Engineering at Sejong University, Seoul, Korea;Dept of Computer Engineering at Konkuk University, Seoul, Korea
Venue:
AI'05 Proceedings of the 18th Canadian Society conference on Advances in Artificial Intelligence
Year:
2005

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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.