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What is DeepFake-o-meter?

An innovative platform equipped with state-of-the-art techniques for identifying deepfakes is now accessible for public use. Users have the capability to upload one video file from their computer at a time. Deepfakes refer to AI-generated altered media that can create deceptive portrayals of individuals and their behaviors, which can lead to serious consequences if exploited. The DeepFake-o-meter, developed by the UB Media Forensics Lab, is an open-source solution aimed at detecting deepfake technologies produced by external sources. It provides an intuitive service that analyzes deepfake content utilizing various sophisticated detection methods, ensuring that results are generated securely and confidentially. In addition, it includes an API framework that allows developers to incorporate their deepfake detection algorithms and run them on a remote server. This platform not only supports developers but also acts as a crucial resource for researchers in the field of digital media forensics, allowing them to evaluate and compare the effectiveness of different detection algorithms. By fostering collaboration and innovation, this comprehensive approach significantly strengthens efforts against the irresponsible use of deepfake technology. As a result, it contributes to a safer digital environment where misinformation can be effectively challenged.

What is DeepFake Detector?

The emergence of deepfake technology presents notable dangers as it allows the production of deceptive videos and audio that can mislead viewers and propagate misinformation. To address this issue, we have developed the DeepFake Detector, a tool designed to assist you in efficiently identifying and filtering out AI-generated content, thereby ensuring the reliability of media in essential areas like journalism and legal proceedings. Understanding the critical consequences of deepfakes, we emphasize the importance of authentic audio and video material. With our expert verification services, you can easily differentiate between genuine media and false representations. To start the verification, choose a video or audio file for evaluation, keeping in mind that the ideal file should last at least 8 seconds and be free of edits or effects to ensure the best possible accuracy. After uploading your selected file, simply click the "detect deepfake" button to commence the analysis, and you will receive a report indicating the probability of the content being a deepfake as opposed to legitimate media. This process empowers you to make educated choices based on the authenticity of the media you are scrutinizing, ultimately promoting a more informed public discourse regarding digital content. Additionally, staying vigilant and aware of the capabilities of deepfake technology can further enhance your ability to navigate the complex landscape of media today.

Media

Media

Integrations Supported

Additional information not provided

Integrations Supported

Additional information not provided

API Availability

Has API

API Availability

Has API

Pricing Information

Free
Free Trial Offered?
Free Version

Pricing Information

$17.88 per month
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

UB Media Forensics Lab

Date Founded

2020

Company Location

United States

Company Website

zinc.cse.buffalo.edu/ubmdfl/deep-o-meter/

Company Facts

Organization Name

DeepFake Detector

Company Website

deepfakedetector.ai/

Categories and Features

Categories and Features

Popular Alternatives

Popular Alternatives

DeepFake-o-meter Reviews & Ratings

DeepFake-o-meter

UB Media Forensics Lab