How many neurons a deep learning model (specifically a CNN) does have? I found total number of neurons of ResNet-50 model is 26,560 and 94,059 in two different papers. Their titles are below:
1: DeepXplore: Automated Whitebox Testing of Deep Learning Systems
2: Testing Deep Neural Network based Image Classifiers
I found another article (link) that clearly describes how many neurons a CNN does have. If I follow this technique then the neuron count does not match with the count mentioned in those papers.
Could anybody please help me how I can calculate number of neurons in a DL model? Also which layers have neurons and which don't have.
I hope you are talking about the parameter count in a convolutional neural network.
Below is basic understanding about calculating the parameters. After getting this, it would be self explanatory.
kernel count = k
kernel size = (a, a)
depth of input = d 
Total number of parameters: k*(a*a)*d + k

Now, for below scenario which has one input layer with one con2d layer.

To cross check the number of parameters, we need k,d,a:
 k = 64, d = 3, a*a = 3*3

Total parameters: 64*(3*3)*3 + 64 = 1792

Hope its clear now.