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Editshare - Enhancing EditShare’s flow media asset management with Automated AI
Nomad

Editshare - Enhancing EditShare’s flow media asset management with Automated AI

Features

Context-rich image analysis for Press archives

February 16, 2023
February 17, 2022
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3
min
Introduction
Find pictures that are newsworthy with one click

Not all pictures speak a thousand words, find the ones that do.

Manual tagging of huge archives is time-consuming and prone to error. Moreover, it’s often difficult to manually sort visuals that have something new, unusual, interesting, or significant in them that would catch the eyes of consumers.

Supercharge your archives using an AI solution that analyses and tags abstract concepts, demographics, brands, events, people, so that finding relevant visuals becomes easy-peasy.

Choose an image tagging system that is fast, accurate, and in-depth.

With Superhuman Vision’s deep visual analysis, you can
- Cut image keywording time by up to 50% compared with other solutions
- Capture abstract concepts like climate change, democracy in crisis, body positivity and keep up with changing socio-political trends
- Maintain balanced demographics in your visuals
- Create custom concepts easily to identify the newest socio–political trends
- Segment videos by highlight scores to identify important scenes

Analyze visual information at scale and speed and use this information for competitive advantage or swift intervention to resolve operational issues.

Want to know more about our Deep Visual Analysis? Read our detailed article here.



Customer details
Solution
Benefits
Written by
Trisha Mandal
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Edited by
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Illustrated by
Xana Ramos

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Mobius Labs GmbH is receiving additional funding by the ProFIT program of the Investment Bank of Berlin. The goal of the ProFIT project “Superhuman Vision 2.0 for every application- no code, customizable, on- premise  AI solutions ” is to revolutionize the work with technical images. (f.e.) This project is co-financed by the European Fund for Regional Development (EFRE).

In the ProFIT project, we are exploring models that can recognize various objects and keywords in images and can also detect and segment these objects into specific pixel locations. Furthermore, we are investigating the application of ML algorithms on edge devices, including satellites, mobile phones, and tablets. Additionally, we will explore the combination of multiple modalities, such as audio embedded in videos and the language extracted from that audio.