Accurate neural network computer vision without the black box

Dec 16, 2020

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“The problem with deep learning models is they’re so complex that we don’t actually know what they’re learning,” said Zhi Chen, a Ph.D. student in Rudin’s lab at Duke. “They can often leverage information we don’t want them to. Their reasoning processes can be completely wrong.”

Rudin, Chen and Duke undergraduate Yijie Bei have come up with a way to address this issue. By modifying the reasoning process behind the predictions, it is possible that researchers can better troubleshoot the networks or understand whether they are trustworthy.

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Accurate neural network computer vision without the ‘black box’https://techxplore.com/news/2020-12-accurate-neural-network-vision-black.html

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