# image classifcation model's depth and width

I wonder how deep and wide deep learning model should be. Where can I possess some information/rules how many layers and how wide they ought to be?

I created basic image classification model with keras in python.

For dataset containig 4 categories: sea coast, highway, parking lot and mountains each containing nearly 1000 images, each category was stored in separated directory named by label. I achived 72% of accuracy.

model = Sequential()



Besisdes of that, I created MNIST digits classifcation, where I achived 95% accuracy with way more shallow and thin model

model=Sequential()