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I'm using the ERFNet Encoder for a project of mine and I had some issues because of the additional conv layer (output_conv). After getting different feature maps every time I ran the network, I realized that this layer didn't have any pretrained weights and I was getting different results because of random initialization. So now I have two questions:
Do you have trained weights for this layer? If that`s the case, could you share them with us? Of course I can use the previous layer as the encoder's output, but the big number of filters is really an issue in my project, so having 20 filters would be much better.
Just out of curiosity, how was this additional layer trained? Did you use a scaled version of the original annotated image as the ground truth?
Thank you very much in advance.
The text was updated successfully, but these errors were encountered:
Hello guys.
I'm using the ERFNet Encoder for a project of mine and I had some issues because of the additional conv layer (
output_conv
). After getting different feature maps every time I ran the network, I realized that this layer didn't have any pretrained weights and I was getting different results because of random initialization. So now I have two questions:Do you have trained weights for this layer? If that`s the case, could you share them with us? Of course I can use the previous layer as the encoder's output, but the big number of filters is really an issue in my project, so having 20 filters would be much better.
Just out of curiosity, how was this additional layer trained? Did you use a scaled version of the original annotated image as the ground truth?
Thank you very much in advance.
The text was updated successfully, but these errors were encountered: