Hi guys!
I meet some problems and hope I could get help from you. My problems are as below:
I wanna design a DCNN to integrate feature maps from different DCNNs for classification. My problem is how to fuse these feature maps? My initial idea is to concatenate these feature maps and then put the big feature map to convolutional layers. However, the number of feature maps from different DCNNs is variable. This makes the in_channels of the Con2d is uncertain after concatenating them.
According to the solution to cope with variable image size, I wanna try the AdaptiveAvgPooling. But it seems this solution need to set the parameter of in_channels of Con2d to None, which is impossible. Right?
Is there any other good solutions? Thank you in advance!