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Elsagate Content Classification in Cartoon Videos

Tatiya, Bhagyashree Sanjay (2020) Elsagate Content Classification in Cartoon Videos. Masters thesis, Dublin, National College of Ireland.

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The tremendous rise in digitization has led to various changes in the daily lives of every individual. Most of the people as well children are very prone to the use of mobile phones now and then. Many kids often watch cartoon either on Television or Mobile phones. Some cartoon videos might contain disturbing scene such as Pornography, Violence which are not appropriate for them to watch. To solve this problem various websites as well applications are launched which were only made for children to watch the cartoon. Although the problem was not solved completely, these scenes were restricted to a great extent. So various techniques have been implemented to solve this problem. The use of Deep Learning Techniques such as VGG-19, Bi-LSTM, Autoencoder is done here to classify the videos into four different categories such as the Sexual, Violent, Both Sexual and Violent and None. This classification of the videos would eventually lead kids to watch cartoon videos without parental support.

Item Type: Thesis (Masters)
Subjects: Q Science > QA Mathematics > Electronic computers. Computer science
T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science
Q Science > QA Mathematics > Computer software
T Technology > T Technology (General) > Information Technology > Computer software
Divisions: School of Computing > Master of Science in Data Analytics
Depositing User: Dan English
Date Deposited: 25 Jan 2021 15:38
Last Modified: 25 Jan 2021 15:38

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