deep learning - Is there any way to change the default output shape of a fully connected layer in a convolutional neural network? -

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i'm reading paper depth prediction using multi-scale cnn.

based on paper, used alexnet or vggnet in first scale.

i'm interested in using vggnet that. there dark points in mind topic. example, can see in following table, output of second fc layer (1.6 & 1.7 fc layers) has strange shape of 19*14:

enter image description here

as understood, fc layers not spatially located, output shape should one-dimensional:

1 * (# of outputs) each sample in mini-batch, (here batch size 16):

enter image description here

so question:

is there way change parameters of fc layer have such dimension (19*14) @ output?

there no such parameters in fc layer, can use reshape layer reshape output size want.

the output of fc layer 64x266. can reshape 64x19x14.

documentation reshape layer: http://caffe.berkeleyvision.org/tutorial/layers.html


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