What do the numbers in this CNN architecture stand for? So I've got a neural net model (ResNet-18) and made a diagram according to the literature (https://arxiv.org/abs/1512.03385). 

I think I understand most of the format of the convolutional layers:
filter dims ,conv, unknown number ,stride(if applicable)

What does the number after 'conv' in the convolutional layers indicate? is it the number of neurons in the layer? 



bonus q: this is being used for unsupervised learning of images, i.e the embedding output a network produces for an image is used for clustering. Would this make it incorrect for my architecture to have an FC layer at the end (which would be used for classifcation)?
This number refers to the number of kernels (or feature maps) that are convolved with the input. So, for example, in the first convolutional layer, $64$ $3 \times 3$ kernels are convolved with the image.

The ResNet presented in Deep Residual Learning for Image Recognition is used for image classification. Furthermore, note that your diagram already contains a fully connected layer at the end.