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In computer vision, how do the layers of the neural netwotk work in order to learn what is visible in an image?
From input to output, the layers gradually move from simpler to more complex forms
Each layer focuses on one aspect: colour, edges, shapes etc.
Nobody really knows what happens inside the neural network but it works!
From input to output, the layers gradually move from complex to simpler forms
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