A Deep Learning-Based Approach for Inappropriate Content Detection and Classification of YouTube Videos

Authors

  • D Navaneetha  Associate Professor, Department of Information Technology, Bhoj Reddy Engineering College for Women, Hyderabad, India
  • K Gangamani  Department of Information Technology, Bhoj Reddy Engineering College for Women, Hyderabad, India
  • A Hymavarshini  Department of Information Technology, Bhoj Reddy Engineering College for Women, Hyderabad, India

Keywords:

Video filtering; Video analysis; Video classification

Abstract

With the emergence of screened films, Video content classification has become ubiquitous. Television films and Internet sites films are a big source of violence that may psychologically hurt teenagers. Although recently, Deep learning video classification has been developed quickly, a Comprehensive survey is needed to summarize the previous work done in this field. Therefore, this survey paper shows the common methods used in video classification. We further discuss the importance of filtering sensitive content such as (pornography, violence, gory, etc.) because of the increasing consumption of films by people of all ages. Several real-world verdict cases are similar scenarios to films with many scenes of violence. As deep learning has shown big success in computer vision areas, researchers are giving it a lot of attention.

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Published

2023-04-30

Issue

Section

Research Articles

How to Cite

[1]
D Navaneetha, K Gangamani, A Hymavarshini, " A Deep Learning-Based Approach for Inappropriate Content Detection and Classification of YouTube Videos, IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology(IJSRCSEIT), ISSN : 2456-3307, Volume 9, Issue 2, pp.666-671, March-April-2023.