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DeepDetector is a deep learning network designed to detect and recognize manipulated faces in images and videos, including deepfakes. This artificial neural network can distinguish between genuine images and computer-generated forgeries by analyzing thousands of real and deepfake images. The technology can extract visible faces in a picture or video, analyze them, and detect deepfake traces with an accuracy rate of approximately 93%. The output of the analysis includes the probability of the input being a deepfake and the Activation Map, which offers an explanation behind the software's decision by substantiating the classification.

DeepDetector not only identifies FaceSwaps and other AI-manipulations but also analyzes characteristics of AI-generated content to detect synthetic media and AI-generated deepfakes. It also provides cloud-based access to customizable APIs so users can integrate DeepDetector into their workflows while complying with data protection laws. Furthermore, DeepDetector's explainable results and accurate detection capabilities make it suitable for various purposes such as KYC compliance, video conferencing, journalism, and penetration testing. Its image analysis time is 1 second with 10+ types of deepfakes detected.

In conclusion, DeepDetector is an effective tool for detecting manipulated faces in images or videos using state-of-the-art technology that ensures data privacy through its compliance with regulations regarding responsible AI practices. It provides reliable results with detailed explanations as well as fast processing times for users to quickly identify potential