1 citations · 1 across the 3 of their papers we have counts for
4 papers
DeBERTa-ConPara: Attack-Aware and Deployment-Realistic Detection of AI-Generated Text
Mohamed Mady, Yupei Li, Johannes Reschke +1
Robust detection of AI-generated text under deployment conditions is challenging: distribution shifts across domains and generators, adversarial perturbations of the input surface,…
Feature-Augmented Transformers for Robust AI-Text Detection Across Domains and Generators
Mohamed Mady, Johannes Reschke, Björn Schuller
AI-generated text is nowadays produced at scale across domains and heterogeneous generation pipelines, making robustness to distribution shift a central requirement for supervised…
Tackling fake images in cybersecurity -- Interpretation of a StyleGAN and lifting its black-box
Julia Laubmann, Johannes Reschke
In today's digital age, concerns about the dangers of AI-generated images are increasingly common. One powerful tool in this domain is StyleGAN (style-based generative adversarial…
Deepfake Detection of Face Images based on a Convolutional Neural Network
Lukas Kroiß, Johannes Reschke
Fake News and especially deepfakes (generated, non-real image or video content) have become a serious topic over the last years. With the emergence of machine learning algorithms i…