In recent years, we have come across a vast range of software tools like "Photoshop" and techniques like DeepFake that have made it easier to create unrealistic and believable face swaps in videos that end up leaving very few traces of manipulation. The...Singh, Aadya...
Efficient deepfake detection using shallow vision transformer CONVOLUTIONAL neural networksMNEMONICSGENERATIVE adversarial networksDeepfake is a deep learning-based technique that generates fake face images by mimicking the ... S Usmani,S Kumar,D Sadhya - 《Multimedia Tools & Applications》 被引量: 0发表...
"Fake face images have been a topic of research for quite some time now, but studies have mainly focused on photos made by humans, using Photoshop tools," Shahroz Tariq, one of the researchers who carried out the study told Tech Xplore. "Recently,a study by Karras et al.showed that a ...
(2021) Realistic face generation using a textual description. In: 2021 5th international conference on computing methodologies and communication (ICCMC). IEEE Wang WY (2017) "liar, liar pants on fire": a new benchmark dataset for fake news detection. arXiv preprint arXiv:1705.00648 Elhadad MK...
Detection of fake news using deep learning CNN–RNN based methods 2022, ICT Express Citation Excerpt : They use Fake News Dataset [16], and as a result, their proposed method is outperformed Ahmad et al. study [15], where the accuracy, precision, recall, and F1-score are 98.36%, 99.40...
paper: [arXiv 2019] Swapped Face Detection using Deep Learning and Subjective Assessment A public dataset comprising 86 celebrities using 420,053 images. This dataset is created using still images, different from other datasets created using video frames that may contain highly correlated images. ...
Deepfake attempts is to use a program that inserts specially designed digital ‘artifacts’ into videos to conceal the patterns of pixels that face detection software uses. These then slow down Deepfake algorithms and lead to poor quality results — making the chances of successful Deepfaking less ...
to capture rich and contextual representations of news texts. By combining natural language understanding with transfer learning and context-based features, the proposed architectures aimed to enhance the detection of fake news. The experiments were conducted using the FakeNewsNet dataset. The results de...
Research on DeepFake detection using deep neural networks (DNNs) has gained more attention in an effort to detect and categorize DeepFakes. In essence, DeepFakes are regenerated content made by changing particular DNN model elements. In this study, a summary of DeepFake detection methods for images...
deep learning methods rely on comparatively larger datasets of top-notch quality, this chapter will also highlight the availability of relevant datasets in this space, as well as share pointers to curate one if needed. Even with sufficient data, however, detection problems in this domain are ...