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Description

DeepDetector is an advanced deep learning network specifically engineered to identify faces that have been generated or altered by AI. Functioning as an artificial neural network, it is adept at uncovering both forgeries and traces left by computer-generated images. This innovative tool plays a vital role in identity verification and fraud prevention. With its exceptional ability to detect AI-generated content, DeepDetector stands as a crucial ally in combating deepfakes. By incorporating biometric systems, it guarantees the authenticity of documents and protects user identity integrity, thereby facilitating Know Your Customer (KYC) processes. Users can achieve rapid and dependable identification of deepfake content in real-time, boasting an impressive accuracy rate of up to 99% and an analysis time of merely one second. Additionally, our versatile API integration allows for smooth customization, enabling the seamless incorporation of our deepfake detection capabilities into your current identity verification frameworks, ensuring you stay ahead in the fight against digital deception. As the landscape of digital content evolves, having such a proactive defense mechanism becomes increasingly essential.

Description

Intel has developed the FakeCatcher deepfake detection technology, which evaluates the “blood flow” in video pixels to quickly assess the authenticity of a video in mere milliseconds. This system is seamlessly integrated into editing software widely used by content creators and broadcasters, allowing for effective detection of manipulated content during the editing process. Furthermore, it serves a critical role in screening user-generated content, ensuring that authenticity checks are part of the upload process. By providing a universally accessible platform for deepfake detection, it empowers individuals and organizations alike to verify the legitimacy of videos with ease. Deepfakes represent synthetic media that distort reality, presenting actors and actions that are fabricated. While many deep learning-based detection systems examine raw data to identify inconsistencies and flaws, FakeCatcher takes a different approach by searching for genuine indicators of authenticity within real footage, focusing on the minuscule evidence of human traits—such as the subtle variations in pixel color caused by blood circulation. When the heart pumps, the color of our veins shifts, creating the unique data that FakeCatcher utilizes to distinguish between real and manipulated videos. This innovative detection method signifies a significant leap forward in the fight against deepfake technology.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

No details available.

Integrations

No details available.

Pricing Details

No price information available.
Free Trial
Free Version

Pricing Details

No price information available.
Free Trial
Free Version

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Vendor Details

Company Name

DuckDuckGoose

Country

Netherlands

Website

www.duckduckgoose.ai/detector

Vendor Details

Company Name

Intel

Country

United States

Website

www.intel.com/content/www/us/en/newsroom/news/intel-introduces-real-time-deepfake-detector.html#gs.08lxwl

Product Features

Product Features

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