this post was submitted on 25 Nov 2023
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Machine Learning

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Hello,

I have a question that may seem trivial but which confused me because I found different approaches to doing it in different papers.

So let’s take the recall as an example : to calculate it on the test set I found two different methods in the codes available for published papers. Some calculate the recall for every image then calculate the mean on all images, other simply use the formula as if each pixel was an element in it’s own. What is the correct way to doing so ?

Thanks in advance !

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[–] puppet_pals@alien.top 1 points 11 months ago

Wrote https://arxiv.org/abs/2207.12120 but never published. I think the "metric definition" is a pretty nice explanation of how it works. Process is the same between bounding boxes & segmentation maps aside from the IoU computation.