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Stream/Area:
-
Subject:
-
Paper ID:
10.55041/IJSREM17515
Volume:
7 |
1 |
Jan 2023
Pages:
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
Everyone now relies on various online social media sources because the internet is so widely used. Social Media video quickly spread among millions of users in a very short period of time along with the increase in the use of social Instagram, Facebook, Twitter, etc. Additionally, spammers use alluring video content to lure readers into clicking on their ads. You occasionally need to confirm the accuracy of information. A new area of research that is receiving a lot of attention is edited video detection. Due to the limited resources, including datasets, processing, and analysis methods, it does, however, face some difficulties. In this work, we suggest a machine learning-based system for detecting edited video detection.
KEYWORDS
Publication Date
1/17/2023
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
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No funding information available for this research.
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