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Crowdsourced Image Classification Will Train AI Models

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A Proof of Concept Grant from the European Research Council for the Picture Pile Platform will provide users with an opportunity to set up and run crowd-sourced image classification campaigns, and then make the images available to train AI algorithms.

ERC Proof of Concept Grants provide top-up funding to ERC grantees to explore the potential of scientific discoveries and bring the results closer to market.

"The new platform will address the gap that currently exists in the market for a platform that allows users to build their own tailored, quality controlled crowdsourcing campaigns to collect image classifications in an efficient, engaging, and fair way, and then possibly make the data collected openly and freely available," says Steffen Fritz, strategic initiatives program director at the International Institute for Applied Systems Analysis, who will lead the project.

While existing image databases can be used to train machine learning algorithms to perform computer vision tasks, there is a lack of datasets containing more specific features of interest. The Picture Pile Platform will address this by building upon the existing Picture Pile crowdsourcing application that allows users to classify or help sort through piles of pictures, which can be very high resolution satellite images, geo-tagged photographs, or any other images that require sorting. After a pile has been sorted, the image classifications can be made publicly available with FAIR (Findable, Accessible, Interoperable, and Reusable) metadata so that they can be freely used by anyone.

The gamified version of the Picture Pile annotation tool is accessible as an online version, and as a mobile app in IOS and Android versions.

From International Institute for Applied Systems Analysis
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