Hi everyone,
I’m designing at the moment my network, which shall classify images relating how many people are in there. So my output dimension is 6 - 0 … 5 people. I’m observing now that the most errors are happening in cases where 4 people are on the image but the network classifies it as 3 or 5. As one idea I would like to define my loss (at the moment I’m using CrossEntropyLoss) in a manner that these cases are more weighted in compare to other cases.
How can you do this?
Thanks and best regards
Jonas