Synthetic Media Detection
Paper Title: Synthetic Media Detection
Authors Name: A. Manoj Kumar , N. Swapna Goud , G. Bhanu Prakash , K. Mithil Reddy
Download E-Certificate: Download
Author Reg. ID: TIJER_101377
Published Paper Id: TIJER2303161
Published In: Volume 10 Issue 3, March-2023
Abstract: Deepfakes are images or videos that have been altered to feature someone else's face, similar to an advanced form of face-swapping. Although some deepfake videos are clearly doctored and inauthentic, the majority appear and sound convincingly real. Deepfake technology has also been used to aid in the spread of false news and other forms of deception. Deep fake detection is a method for detecting face tampering in videos that focuses on two recent techniques used to generate hyper realistic forged videos: Deepfake and Face2Face. Traditional image forensics techniques are typically unsuitable for video due to the compression, which severely degrades the data. As a result, this paper takes a deep learning approach and presents two networks with a low number of layers to focus on image mesoscopic properties. We test those fast networks on an existing dataset as well as a dataset created from online videos.
Keywords:
Downloads: 000189
Page No: 230-239
Country: Peddapalli, Telangana, India
Research Area: Science and Technology
Published Paper URL: https://tijer.org/TIJER/viewpaperforall?paper=TIJER2303161
Published Paper PDF: https://tijer.org/TIJER/papers/TIJER2303161
ISSN:
2349-9249 | IMPACT FACTOR: 8.57 Calculated By Google Scholar| ESTD YEAR: 2014
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.57 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
Publisher: TIJER(IJPublication)
Click Here to Download This Article
Article Preview
