Abstract
The volatile growth of social media content on the Internet is revolutionizing content distribution and social interaction. Social media exploded as a category of online discourse where people create content, share it, bookmark it and network it at prodigious rate. Examples comprise Facebook, MySpace, Youtube, Instagram, Digg, Twitter, Snapchat and others. Since it is easy to reach, use and the high velocity of spreading information among users. The internet as it is at present is made up of a vast array of protocols and networks where traffickers can anonymously share large volumes of illegal material amongst each other from locations with relaxed or non-existent laws that prohibit the possession or trafficking of illegal material. In this paper, a review of applications of deep networks techniques has been presented. Hence, the existing literature suggests that we do not lose sight of the current and future potential of applications of deep network techniques. Thus, there is a high potential for the use of Convolutional Neural Networks (CNN) for violence video classification, which has not been fully investigated and would be one of the interesting directions for future research in video classification.
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This research funded by Ministry of Higher Education Malaysia MyBrain 15. This paper also was partly sponsored by the Center for Graduate Studies UTHM.
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Ali, A., Senan, N. (2017). A Review on Violence Video Classification Using Convolutional Neural Networks. In: Herawan, T., Ghazali, R., Nawi, N.M., Deris, M.M. (eds) Recent Advances on Soft Computing and Data Mining. SCDM 2016. Advances in Intelligent Systems and Computing, vol 549. Springer, Cham. https://doi.org/10.1007/978-3-319-51281-5_14
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