Deep learning uses its capacity to recognise complex patterns and features in data to increase the accuracy of deep-fake detection. Convolutional neural networks (CNNs), in particular, are deep learning models that are capable of detecting minute irregularities and artifacts in pictures and videos ...
Currently, face-swapping deepfake techniques are widely spread, generating a significant number of highly realistic fake videos that threaten the privacy o... A Ismail,M Elpeltagy,MS Zaki,... - 《Sensors》 被引量: 0发表: 2021年 Deepfake Detection Approaches Using Deep Learning: A Systematic ...
Much research has been devoted to developing detection methods to reduce the potential negative impact of deepfakes. Application of neural networks and deep learning is one approach. In this paper, we consider the deepfake detection technologies Xception and MobileNet as two approaches for ...
Deep fake detection using cascaded deep sparse auto-encoder for effective feature selection In the recent research era, artificial intelligence techniques have been used for computer vision, big data analysis, and detection systems. The developmen... SB Balasubramanian,KR Jagadeesh,P Prabu.,... - ...
There are several approaches to using neural networks for deep fake detection. One approach is to use a convolutional neural network (CNN) [1] to analyze the visual artifacts in the image or video. The CNN can detect inconsistencies or anomalies in the image or video that are indicative of ...
【3.1 – Fake Image Detection】 人脸交换在视频合成,人像变形,尤其是身份保护方面具有许多引人注目的应用,因为它可以用图片库中的人脸替换照片中的人脸。但是,它也是网络攻击者用来渗透识别或身份验证系统以获取非法访问的技术之一。诸如CNN和GAN之类的深度学习的使用,使交换的面部图像对于取证模型更具挑战性,因为它...
摘要 Deep learning-based approaches are applied successfully in manyfields such as deepFake identification,big data a...展开更多 作者 R.Saravana Ram M.Vinoth Kumar Tareq M.Al-shami Mehedi Masud Hanan Aljuaid Mohamed Abouhawwash 机构地区 Department of Electronics and Communication ...
Detection of Fake News Text Classification on COVID-19 Using Deep Learning Approaches. we applied eight machine-learning algorithms such as Naive Bayesian, Adaboost,K-nearest neighbors, random forest, logistic regression, decision tree, neural networks, and support vector machine and four deep ...
Fake news detection is very difficult while its spread is simple and has vast repercussions. To tackle this problem we propose a model which detects fake information and news with the help of Deep Learning and Natural Language Processing. A Deep Neural Network on self scraped data set is traine...
Fake news detection using deep learning Final master thesis projectThis repository is focused on finding fake news using deep learningThere are multiple methods focused on achieving this goal, but the objective of this work is discriminating the fake ones by only looking at the text. No graphs, ...