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4 years ago I posted this question and got a few answers that were unfortunately outside my skill level. I just attended a build tour conference where they spoke about machine learning and this got me thinking of the possibility of using ML as a solution to my problem. I found this on the azure site but I don't think it will help me because its scope is pretty narrow.

Here is what I am trying to achieve:

I have a source image:

source image

and i want to which one of the following symbols (if any) are contained in the image above:

symbols

the compare needs to support minor distortion, scaling, color differences, rotation, and brightness differences.

the number of symbols to match will ultimately at least be greater than 100.

is ML a good tool to solve this problem? if so, any starting tips?

1 Answer

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by (9.6k points)

1. Create your data set with positive and negative examples from a fixed window size. 

2. Choose a classification algorithm and train the model. Here, your algorithm will read the images and create vectors and label them. Do not forget to split the data into training and testing data sets.

3. Run the model until it manages to learn itself. 

Once you are good to go, you can try out other algorithms to increase the efficiency. 

ML is sure a good tool to get started with. 

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