# how to add the pool4 to the 2 x conv7 in FCN-16s using keras?

Now I'm using tensorflow.keras to implement the FCN-16s,

this picture may be different with others, you should focus this it add pool4 to 2x conv7 not 2x pool5 in FCN-16s. Actually the conv7's output_shape is (w/32,h/32,classes_number) in my implementation. I know conv7 should multiply 2 to achieve the same shape (1st,2nd) with pool4. But my question is the pool4's shape is (w/16,h/16,512), ps 512 is the output_channel of the last conv-layer. pool4 and 2x conv7 have not same shape(3rd), how to add?

And another question is what are the train-labels for the FCN, I think a train-label is just a image which has the same width and same height with input_image and has classes_number channel to show each pixel's possibility belong to each class. This idea is derived from the conv7's output_shape, is it right? I hope you can give me more and clear explanations. Thanks!!!

• You should post implementation questions on either DataScience or StackOverflow. – Philip Raeisghasem Apr 3 '19 at 1:04
• emm, I don't think it is a implementation question entirely. The main point is that I hope someone could give me a clear explanation about how to add pool4 to 2x conv7 which have the different 3rd-shape. If I fix up this, the implementation become easy.Thanks! Actually, I have asked some questions about DL on stackoverflow, but someone let me to ask here due to he thinks these questions are related with mathematics. – kakaw95 Apr 3 '19 at 1:22