This isn't really a theano question and might get more traction elsewhere. Have you considered adding a "no action" class to your problem for the frames/times where nothing is happening?
On Thursday, September 15, 2016 at 8:15:01 AM UTC-7, aditya vora wrote: > > Hello , > > We are training a 3D convolutional neural network with real life videos > that we recorded from cameras. Actually, my dataset has around 3000 video > clips which are obtained by dividing a single surveillance video. Each clip > was appropriately labelled by us. I need to classify this videos into > different actions. However, as the data is obtained by capturing real life > videos it is certainly not possible to have totally clean data, as a > result, there are certain situations in the video clips in which there are > no actions happening. However we tried to remove such clips as much as > possible but still couldn't filter out all clips because some frames of the > same clip had actions in it (Eg. Person running and going out of the > frame). So my question is how the convolutional neural network training > shall behave in such a situation? Will the network be immune to such > "outliers" as most of the data is appropriate? If it will affect the > training then how it shall affect and if not how? I need a mathematical > proof to this question in terms of parameter update and stuff. > > Thanks, > With Regards, > Aditya Vora > -- --- You received this message because you are subscribed to the Google Groups "theano-users" group. To unsubscribe from this group and stop receiving emails from it, send an email to [email protected]. For more options, visit https://groups.google.com/d/optout.
