• Mrs. Jala Sravanthi
• Mrs. Anugu Divya
• Mr.Amgoth Shiva
• Mr. Arrolla Nithin Prakash

As more movies and videos are made available, it's important to think about how we classify them to protect young people. We're seeing a lot of violence in TV shows, movies, and online videos, which can be harmful to teenagers. Thanks to advances in technology, especially deep learning, we can now better analyze and categorize videos. However, there's still a need for a comprehensive review of the methods used so far. This paper aims to summarize what researchers have been doing in this area. We'll look at how videos are typically classified and why it's important to filter out certain types of content, like violence and explicit material. People of all ages are watching more videos than ever before, so it's crucial to make sure they're not being exposed to harmful content. We'll also discuss real-life examples where violence in movies has led to legal issues. With deep learning becoming increasingly powerful in fields like computer vision, it's becoming a key tool in video classification research.

Deep learning, video content classification, inappropriate content detection, YouTube videos, violence, sensitive content filtering, computer vision, teenagers, film consumption, real-world verdict cases.

"A Deep Learning-Based Approach for Inappropriate Content Detection and Classification of YouTube Videos", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 3, page no.f171-f175, March-2024, Available :http://www.jetir.org/papers/JETIR2403521.pdf

"A Deep Learning-Based Approach for Inappropriate Content Detection and Classification of YouTube Videos", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 3, page no. ppf171-f175, March-2024, Available at : http://www.jetir.org/papers/JETIR2403521.pdf