基于视频的假新闻检测技术综述

Ronak Agrawal, D. Sharma
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引用次数: 7

摘要

在当今世界,假新闻识别是一个关键问题。假新闻可能以文字、图片和视频的形式存在。目前存在几种检测假新闻的技术,包括伪造检测技术。本文讨论了现有的用于假视频检测的伪造技术。在本研究中,我们解决了现有的问题和挑战,使伪造检测任务繁琐。讨论了深度神经网络、卷积神经网络、生物信号和时空神经网络在假视频识别中的应用。还提供了用于伪造检测的现有技术的比较研究。这项详尽的调查将有助于其他研究人员解决深层次的假问题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Survey on Video-Based Fake News Detection Techniques
In today's world, fake news identification is a critical problem. Fake news may exist in form of text, images and videos also. There are several techniques exist for fake news detection including forgery detection techniques. This paper discussed the existing forgery techniques used for the fake video detection. In this study, we addressed the existing issues and challenges which make the forgery detection task cumbersome. We have discussed the use of deep neural network, convolutional neural network, biological signal and spatio-temporal neural network for fake video identification. A comparative study of existing techniques, used for forgery detection, is also provided. This exhaustive survey will help the other researchers to combat deep fake problem.
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