DeepDetector employs a deep learning network engineered to spot and identify manipulated faces, such as deepfakes, in both images and videos. By examining a large number of authentic and deepfake visuals, this neural network is capable of discerning between real images and those generated by computers.
The technology has the capacity to isolate visible faces within an image or video, analyze them, and detect traces of deepfakes with approximately 93% accuracy. The results include the likelihood of the input being a deepfake, accompanied by an Activation Map that explains the software's assessment by supporting its classification. DeepDetector is able to not only recognize FaceSwaps and other forms of AI-based manipulation, but it can also evaluate the attributes of AI-generated content in order to identify synthetic media and AI-created deepfakes.
The tool provides cloud-based access to adaptable APIs, allowing users to incorporate DeepDetector into their existing processes. It prioritizes data security and privacy by adhering to European laws and regulations concerning data protection, privacy, and responsible AI. DeepDetector finds applications in areas like KYC compliance, video conferencing, journalism, and penetration testing.
Designed for both accuracy and interpretability, the tool identifies over 10 types of deepfakes and completes image analysis in just 1 second. To summarize, DeepDetector serves as a robust and dependable solution for identifying deepfakes and other AI-based manipulations in images and videos.
Detects faces that have been altered.
Examines a vast amount of images.
Achieves a 93% accuracy level.
Inconsistent accuracy rates
Detection limited to faces
Limited detection of deepfake types

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