I have a problem where I wish to classify each column in an image of a feature being present (1) or absent (0) in each column. The output of the model should be a vector of size of the width of an image. I am trying to consider how the output of a CNN would look for such a network. I assume I would use a sigmoid loss function due to being a binary classification task. I can see how it would be possible to output a single 1 or 0 from the output of the sigmod function. However, I cannot seem to figure out how I would be able classify each column in the image. Would anyone have any ideas on how to implement this? I believe I do not have the correct idea of the fully connected layer and/or sigmoid function. Would appreciate any help in understanding this.