You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
hello :
I am very glad to see your public your model, I have already seen your paper, there is a question to ask you, you mentioned in the paper “It is also found helpful to clip the gradient to constrain the
norm within [−0.1, 0.1] ”.It means the solve parameter which called "clip_gradient" is among [-0.1,0.1]
The text was updated successfully, but these errors were encountered:
Sorry for the late reply, yes it is, and you can find the related work using "clip_gradient" in "Accurate Image Super-Resolution Using Very Deep Convolutional Networks". It is of great importance during training AOD-Net. Hope this helps.
hello :
I am very glad to see your public your model, I have already seen your paper, there is a question to ask you, you mentioned in the paper “It is also found helpful to clip the gradient to constrain the
norm within [−0.1, 0.1] ”.It means the solve parameter which called "clip_gradient" is among [-0.1,0.1]
The text was updated successfully, but these errors were encountered: