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==Deep learning== The term [[deep learning]] has variable meanings, most of which can be applied to techniques used in machine vision for over 20 years. However the usage of the term in "machine vision" began in the later 2010s with the advent of the capability to successfully apply such techniques to entire images in the industrial machine vision space.<ref name = qualitymag2022>''The Place for Deep Learning in Machine Vision'' Quality Magazine May 2022 issue, Volume 61, Number 5 Published by BNP Media II</ref> Conventional machine vision usually requires the "physics" phase of a machine vision automatic inspection solution to create reliable ''simple'' differentiation of defects. An example of "simple" differentiation is that the defects are dark and the good parts of the product are light. A common reason why some applications were not doable was when it was impossible to achieve the "simple"; deep learning removes this requirement, in essence "seeing" the object more as a human does, making it now possible to accomplish those automatic applications.<ref name = qualitymag2022/> The system learns from a large amount of images during a training phase and then executes the inspection during run-time use which is called "inference".<ref name = qualitymag2022/>
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