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Analyzes doctored media.
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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 can not only identify FaceSwaps and other AI-manipulations but also analyze characteristics of AI-generated content to detect synthetic media and AI-generated deepfakes.

The tool also offers cloud-based access to customizable APIs to integrate DeepDetector into user workflows, ensuring data protection and privacy through compliance with European laws and regulations regarding data protection, privacy, and responsible AI.DeepDetector can be used for compliance purposes such as KYC, video conferencing, and journalism, as well as in penetration testing.

The tool is designed to provide explainable and accurate results, with 10+ deepfake types detected and an image analysis time of 1 second. In summary, DeepDetector is a powerful and reliable tool for detecting deepfakes and other AI-manipulations in images and videos.

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Duckduckgoose was manually vetted by our editorial team and was first featured on April 13th 2023.
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Pros and Cons

Pros

Detects manipulated faces
Analyzes thousands of images
93% accuracy rate
Cloud-based access
Customizable APIs
Compliance with European laws
Data protection and privacy
Useful for compliance purposes
Useful for video conferencing
Useful for journalism
Useful for penetration testing
Explains results
Detects 10+ deepfake types
Image analysis in 1 second
Trained on representative datasets
93% correct predictions
84.37% precision in fake classifications
92.57% recall in fake predictions
Detects synthetic media

Cons

Accuracy rate inconsistency
Detection limited to faces
Limited deepfake types detection
No offline capabilities
Requires API integration
Reliant on European regulations
User interface not mentioned
No performance on video content
Long term efficacy unproven
No information on speed

Q&A

What is the main function of DeepDetector?
How does DeepDetector detect fake images or videos?
What is the accuracy rate of DeepDetector?
What is the Activation Map in DeepDetector?
Does DeepDetector offer API integrations?
What is the image analysis time for DeepDetector?
What types of deepfakes can DeepDetector detect?
How does DeepDetector ensure data protection and privacy?
Can DeepDetector detect AI-generated content?
How can DeepDetector be used in KYC compliance?
What is the purpose of the Activation Map feature in DeepDetector?
Can DeepDetector be integrated into my existing workflow?
What is the precision percentage of DeepDetector?
How does DeepDetector substantiate its classifications?
Does DeepDetector comply with European data protection laws?
What is the meaning of DeepDetector's 'Explainable Results' feature?
Can DeepDetector detect FaceSwaps and other AI-manipulations?
What are the steps DeepDetector uses to detect a deepfake?
How does DeepDetector analyze a detected face to find deepfake traces?
What is the Retention and Compliance feature of DeepDetector?

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