In The News

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Research Feature

The research behind Vision Semantics' technology is featured in this article by Queen Mary University of London. 

"Professor Gong is a pioneer of computer vision and machine learning for visual surveillance, and a world authority on Person Re-Identification. His Computer Vision research group are internationally renowned for their work on unusual behaviour recognition, person re-identification, multi-camera tracking, video search and categorisation, and face analysis in video and images."

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IET Award

Professor Sean Gong from Queen Mary University of London has been awarded the Achievement Medal for Vision Engineering, one of the Institution of Engineering and Technology's (IET) Achievement Awards.

The IET Achievement Awards, which recognise some of the world's top engineering talent, acknowledge individuals who have made an exceptional contribution to the advancement of science, engineering and technology in any sector, either through research and development in their respective technical field or through their leadership of an enterprise.

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QMUL

Professor Sean Gong has been ranked 19th for Computer Science in the UK by 'Guide 2 Research' in their Leading Computer Scientist List. This ranking lists all leading computer scientists affiliated with the United Kingdom and includes other eminent computer scientists from the Alan Turing Institute and its partner universities.

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CVPR 2020

Vision Semantics has been working on applying computer vision capability to ecommerce applications and modifying the search with text feedback. Professor Gong completed a project with Amazon Berlin which led to a presentation at CVPR in Seattle June 16-18, 2020.

The paper was also featured in the latest Amazon Science AI Blog:

https://www.amazon.science/blog/how-computer-vision-will-help-amazon-customers-shop-online

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The Batch

Vision Semantics work on text based attention search has been featured by Andrew Ng, in the  AI in Focus newsletter, The Batch. 

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MIT University

Deep learning for the development and training of large AI models is reaching its limits. This is what researchers at the American University MIT concluded in a recent study. The reason for this is that the required computing power can no longer grow. Vision Semantics recognised this issue 4 years ago and began development of an alternative approach, exploiting AI on small data in distributed data sets.
 

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Associated Press

The European Union’s top court ruled on 16th July 2020 that an agreement that allows companies to transfer data to the United States is invalid. The ruling to invalidate Privacy Shield will likely complicate businesses who centralize their data and use AI model on centralized data training sets. 

Vision Semantics approach to keeping data private in distributed environments, but allowing the AI model to continue to learn is an alternative approach to dealing with this EU ruling.