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AI Deepfake Detection Made Easy with DeepDetector Software

DeepDetector is a deep learning network designed and trained to recognise AI-generated or AI-manipulated faces. DeepDetector can be seen as an artificial neural network designed to spot forgeries and traces generated by computers.

It serves as a critical tool in verifying identities and preventing fraud. DeepDetector is especially adept at detecting AI-generated content, making it an essential asset in the fight against deepfakes. Through the integration of biometric systems, it ensures the authenticity of documents and safeguards the integrity of user identities, supporting KYC (Know Your Customer) processes.
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AI image and video detector

01. Extract

The first step towards deepfake detection is extracting all visible faces in the picture or the video.

02. Analyze

After detecting the face(s), our deepfake detection technology gets activicated and analyzes the faces to find deepfake traces.  

03. Detect & explain

The output of the analysis includes the probability of the input being a deepfake and the Activation Map to substantiate the classification.

1 Sec

Image analysis time


Explainable results




Deepfake types

How can our AI Deepfake Detector help?

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Fast & Accurate

Get quick and reliable identification of deepfake content in real-time with our accuracy rate of up to 99% and lightning-fast analysis time of just 1 sec
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Our flexible API integration empowers you to seamlessly customize and integrate our deepfake detection solution into your existing identity verification systems
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Comprehensive Deepfake Detection

Our advanced AI algorithms are designed to detect a wide range of deepfake techniques, including face swaps, lip-syncing, and manipulated audio
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Our advanced AI algorithms checks videos and images for signs of manipulation and provide detailed explanations of any detected deepfakes, allowing you to take appropriate action

How DeepDetector detect deepfakes

How our Deepfake detection software, DeepDetector works
DeepDetector detects deepfake faces in videos and pictures with an accuracy of 95%. Our technology does not only classify an input as fake, but also explains the reasoning behind its decision by using Activation Maps. It is able to do this, because the DeepDetector has seen hundreds of thousands of real and deepfake images. It has trained itself on these images and has learned to find the subtle differences between a photo made with a real camera or a photo synthesised by a computer.

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What can DeepDetector detect?

Deepfake manipulated media

DeepDetector scans and filters FaceSwaps and various other AI-manipulations by looking for traces of alterations in existing (camera-made) pictures and videos.
Tom Cruise deepfake
This person does not exists

Synthetic media and AI-generated deepfakes

AI-generated visual content, such as StyleGANs are not distinguishable for the unaided human eye. DeepDetector analyses characteristics of AI-generated content to detect them.
Liveness check vs AI deepfake detection

What sets us apart?

Most current digital identity solutions can identify common methods of attack, such as the OBS virtual camera. However, when the attack methods get more advanced, these systems are prone to get fooled. With countless unknown attack methods out there, the chances of deepfakes being mistaken for a real person increases.
DuckDuckGoose offers a solution to this problem, as our software is built to detect the actual fake content itself rather than just how it's being presented. This means we are able to provide a more reliable and effective solution, even when faced with advanced or unknown attack methods.

92.93% Accuracy

Percentage of correct predictions (of both real and fake)

84.37% Precision

Percentage of fake classifications that were actually fake

92.57% Recall

Percentage of actual fakes that are correctly predicted

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AI deepfake checker detecting celebrity deepfakes of elon musk in star trek