Deepfake images, created through advanced AI techniques, pose significant cybersecurity risks, facilitating identity fraud and potentially damaging reputations and financial stability. The primary ...

A hybrid deep learning model combining EfficientNet and Vision Transformers for accurate deepfake image detection. Trained on FF++ and DFDC datasets, the model improves feature extraction, ...

The notebook evaluates model performance on training, validation, and test sets and calculates the F1 score. The final model is saved (e.g., as my_trained_model.h5) for later inference. Inference & ...

Image forgery, as a classic form of academic mis-conduct, has garnered increasing interest from researchers in the field of research integrity. Concurrently, automated detection and localization ...

AI detects objects in images by using computer vision techniques that analyze the visual features of an image. The process typically involves using a convolutional neural network (CNN) to identify ...

Google optimized these models to embed watermarks that align with the original image content, maintaining visual quality while enabling detection. In internal testing, SynthID accurately ...

Use an AI image detection tool. Similarly, AI detection tools can extract watermarks and metadata from uploaded images to determine whether a piece of media is from a genuine source or created by a ...

AI-generated images can spread misinformation and fool the public, but ChatGPT maker OpenAI says its new tool can root out fake pictures with unerring accuracy. Skip to main content Menu ...

OpenAI is working on an image classifier that will detect characteristics of a DALL-E 3-created image. It will also add watermarks to audio clips.

LinkedIn has developed a new AI image detector research concept that has a 99% success rate in catching fake profile photos, with a 1% false positive rate.