I am a starter in ML and I need some help...
Assume that I have a classifier which can classify left hand / right hand well. I am curious whether it can decide whether there's a hand in the image?
Because if it is not the case, I have to collect additional data that are labeled as "no-hand". But there's so many things that are "no-hand" such like dogs, cats, flies... I don't think it is possible to collect all those possible "no-hand" data..
Would it be reasonable that we use some activation functions like [sigmoid] as the final outputs for the classifier(neural network) and we consider the outputs for both left/right classes as the scores that classifier think how far the input is from the left/right hands classes.
Then if the outputs are below some threshold for both left hand and right hand we can say there's no hand in this image input.