Tag: deepfake detection

A new study shows that feeding wavelet sub-bands into a standard ResNet-50 improves fake-class sensitivity and F1 in cross-forgery deepfake ...

The finding that ear visibility dominates the attribute landscape of DeepFake detection errors deserves closer scrutiny, because it connects to ...

Researchers have developed FedHybrid-ViT, a privacy-preserving framework that fuses convolutional and transformer models within federated learning to detect deepfakes across ...

Researchers have introduced Light-wDEF, a resource-efficient and fully reproducible framework that enabled a fair comparison of ten visual deepfake detectors ...

A new systematic review finds that hybrid deep learning and metaheuristic optimization frameworks achieve 98 to 100 percent accuracy in ...

Researchers developed a lightweight CNN-LSTM model that detects deepfake videos with high accuracy on standard hardware.

A controlled comparison shows attention-enhanced DenseNet121 reaching 97.4 percent accuracy for deepfake detection while a lighter MobileNetV2 variant offers a ...

A new composite scoring framework called RECAF jointly measures deepfake detectors' accuracy, robustness to image distortions, and cross-dataset generalization, revealing ...

A multimodal AI model called ERF-BA-TFD+ detects and localizes audio-visual deepfakes by cross-reconstructing audio and video features and reasoning over ...

Researchers have introduced Aperture, a lightweight AI framework that jointly detects deepfakes and localizes tampered regions while adapting to unseen ...