How can a CNN exploit knowledge about (almost perfect) structure of objects it needs to detect?

Hi!

For my deep learning class I need to design a CNN that can detect Plants on a field, similar like in this video [https://www.youtube.com/watch?v=ijAfvd6S6-A](https://www.youtube.com/watch?v=ijAfvd6S6-A)

I designed a working CNN, based on transfer learning with a mobilenetV2 architecture, which works fine on the dataset. One of the questions, however, is to explain how such a CNN could exploit the (almost perfect) regular placement of plants in the field.

Do you have any ideas what my professor would like to hear …

cnn deeplearning knowledge objects