Deepfake Detection System

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Key Benefits

  • Educational
  • Deepfake Detection

Key Technologies Used

  • Python
  • HTML
  • CSS

Project Background & Description

Today, Deepfake technology is widely available, leading to an increase in manipulated content across the internet. These realistic fakes can make it appear as though someone said or did something they never actually did, blurring the line between fact and fiction. To address this growing concern, we’ve developed a deepfake detection website to help users identify deepfakes and protect themselves from misinformation.

Our platform features three advanced deepfake detection models trained to analyze images, videos, and audio. Each prediction includes a confidence percentage, helping users assess the likelihood of manipulation. Additionally, the website includes an educational section where users can learn about deepfakes and tips for spotting them. To reinforce their learning, users can take a quiz to test their ability to detect deepfakes in images and videos. The history page provides easy access to previously analyzed files, allowing users to review their results and track their progress.


Project Team Members

Aung Kaung Myat​

Aung Kaung Myat​

Nigel Chee Yi​

Nigel Chee Yi

Nur Hidayah Binte Johar

Nur Hidayah Binte Johar​

Yee Yi Yang Kenneth​

Yee Yi Yang Kenneth

Supervisor

Jet Lim (Mr)

Industry Partner

Temasek Polytechnic

Temasek Polytechnic School of IIT, Follow us on our Social Media