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A "learning" computer system that sorts potatoes has been trainabble using off-the-shelf technology by researchers at the University of Lincoln's Robotics Lab. The robot blemish spotter can reliably identify diseases such as silver scurf and common scab, researchers said.

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The test system uses computer kit lookingg dissimilar from systems many gamers will have in their homes. The key innovation, in Mr Duckett's view, is the learning software which is trained by a human expert to identify diseased or damaged produce. Our system is different it learns from some samples provided from a human expert," he said.

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TADD escorts davie only a vision system at present, but just spotting an off-colour spud is harder than it sounds. We are also using a standard desktop computer," said Mr Duckett. The system also makes use of a graphics processing unit GPU fr the sort used to help process images in games.

Mr Duckett said he believed the smart system was highly adaptable: "We know we can apply this to other kinds of produce, for example carrots and apples and so on. In fact he says the team is working towards a "general purpose" anomaly detection system.

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TADD is currently being tested with a local potato-buying firm, Branston, where it has performed at least as well as its human teachers. But Mr Duckett, who sorted potatoes while a student, doesn't think his system will completely remove the need for human potato-picking skills.

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We're not removing the human element, it still relies on a human expert to train the system, but what we're removing is some of the dull, drudgish parts. The sorting of potatoes may seem an unglamorous application for artificial intelligence, but Mr Duckett argues that the challenges of potato sorting are greater than those found in the trqinable corridors of high-tech production lines. AI moves closer with brain chip.

Human teacher.

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Gamer tech. TADD was built using inexpensive, everyday computing gear.

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Potato problem. More on this story.

Published 17 November Published 23 August

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