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An Image similarity solution to track online image thefts

“Our client objective is to immerse machine learning-powered image similarity application to help people and businesses to identify and protect their image and video copyrights."

Problem

The client is a US-based firm that runs a digital platform for creatives and photographers to share, upload and discover where and how images published by them are being used online. The primary objective of the project is to develop a machine learning model that can seamlessly identify similar images and record the unauthenticated usage of images across the web.

Challenges

As mentioned earlier, the key challenge is to prevent the photographers’ and image creators’ work from being stolen or being used unauthorizedly on various platforms. However, it is impossible to completely prevent such crime in digital space but, there are a few ways to mitigate this risk by applying AI and Machine Learning to model building.

Solution

Our team of experts at SoulPage built an ML-based image recognition and identification model for defining similarities between images (the one uploaded and the one found on the web) to accurately rate and describe further actions to be taken to prevent thefts.

  • The model allows the uploading of new images and watches out for the digital spaces with similar images.
  • AI-powered filters to categorize and automatically group similar image matches identified.
  • Auto-generated notifications (when new images matching your search are detected) to keep you updated.

Tools & Technologies

ML, CNN, Django, Golang, Kafka

Impact

  • Preventing unauthorized usage of digital images
  • Copyright authentication
  • Privacy and preservation of data on images

Product: Image similarity ML algorithm

Company: Pixsy GmbH

Location: Berlin, Germany

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    Product: Image similarity ML algorithm

    Company: Pixsy GmbH

    Location: Berlin, Germany

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