0
$\begingroup$

I read some papers about state-of-the-art semantic segmentation models and in all of them, authors use for comparison F1-score metric, but they did not write whether they use the "micro" or "macro" version of it.

Does anyone know which F1-score is used to describe the segmentation results and why it is so obvious that authors do not define it in papers?

Sample papers:

https://arxiv.org/pdf/1709.00201.pdf

https://arxiv.org/pdf/1511.00561.pdf

$\endgroup$
0
$\begingroup$

I looked very quickly and only at the first paper so I might miss something but it looks to me like the task is a binary classification problem. If this is correct then there's no need for averaging the F1-score.

Also in this paper the authors even give the formula of the F1-score (!), so I'd say that they are quite thorough in their description of the evaluation measures they use. I would take this as an additional indication that there's no averaging, since it's unlikely that they wouldn't mention it.

$\endgroup$

Your Answer

By clicking “Post Your Answer”, you agree to our terms of service, privacy policy and cookie policy

Not the answer you're looking for? Browse other questions tagged or ask your own question.