How to determine number of Neurons setup in Convolutional Neural Networks?
A typical best practice is to read related papers or check github projects with information about similar architectures and how other ML engineers structured them. Usually, you can see some certain patterns in CNN architectures like increasing the depth along the pipeline (or number of channels) while decreasing width and height of results in each layer. Since the search space is huge and time so limited, it is usually better to rely upon already made architectures, and use, if possible, transfer learning to shorten training cycles. On the other hand, if you are doing pure research and want to create your top-notch, new state-of-the-art CNN architecture, you will need to carry out a very big effort on CNN architecture engineering as well as hyperparameter tuning, luckily on a systematic basis.