MATLAB: Image Processing with Backpropagation algorithm

Question

First of all, I don't have the code yet for this project. I just want to ask first what would be the good approach/way to do this project before I start with the code (although I'm not that good in MATLAB). So our project is to determine the shades of green of the leaves and the shape of the diseases present on the leaves. What we have proposed so far is to make a database for the shape and color using the backpropagation. And then the test image will be compare to the database. Do you think that's a good approach? Can you suggest some other approach to do this better.

Thank you and God bless 🙂

Answer 1

Backpropagation is not used to directly create a data base.

However, if you have a data base of inputs and targets, one of the backpropagation functions like fitnet (regression or curvefitting) or patternnet (classification or pattern recognition) is used to NOT ONLY output close approximations to training target vectors when the corresponding training input vectors are presented, BUT, more importantly, generalize to nontraining data.

Backpropagation can be used to create nets for testing whether or not your choice of targets and target coding (real?, max? min? binary? unity sum? etc) is useful.

Hope this helps.

Thank you for formally accepting my answer

Greg