Image Processing with Backpropagation algorithm
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Elvin
el 8 de Sept. de 2013
Comentada: Image Analyst
el 28 de Abr. de 2014
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 :)
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Greg Heath
el 14 de Sept. de 2013
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
2 comentarios
Greg Heath
el 18 de Sept. de 2013
Editada: Greg Heath
el 18 de Sept. de 2013
You should post a new question on how to implement image feature extraction in order to create a data base of shape and color features.
Más respuestas (3)
Shashank Prasanna
el 8 de Sept. de 2013
Hi Elvin, what you are proposing is a supervised learning approach. backpropogation (Neural Networks) to train your data is one good approach. You could also explore other supervised learning approaches in the statistics toolbox:
Because of the convenient way the functions have been written, its easy to just try different algorithms quickly that saves you time.
Here are some good ways to get started:
3 comentarios
Shashank Prasanna
el 16 de Sept. de 2013
Editada: Shashank Prasanna
el 16 de Sept. de 2013
backpropogation can be used to train on a dataset for future prediction and is a popular approach. You can use the Neural Network Toolbox to do that.
It is not clear what you mean when you say "make the color and shape database"
primrose khaleed
el 27 de Abr. de 2014
i want create database of image and i want to enter this image into NN..my asking which image saving in database ?? the original images or after fuature extraction?
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