<p>Maybe, but it's likely overkill.  In hyperparameterization, random search, successive-halving or, lastly, evolutionary optimization is generally more than enough.  This is not to mention the dozen other methods people have proposed over the years.</p>

CC BY-SA 4.0
2024-12-23T19:09:09.820Z
2024-12-23T19:09:09.820Z
foreverska
<p>I've developed a computer vision algorithm that produces a binary result from an image. This algorithm depends on a number of parameters.</p>
<p>Is it possible to use a neural network to learn the best parameters, given the outcome of the execution of the algorithm on several images?</p>

CC BY-SA 4.0
2024-12-23T13:56:52.960Z
are these parameters dependent on the image you are processing or they should be something generic?
Alberto
<neural-networks><computer-vision>
Can a neural network be used to find the best parameters of an algorithm?
user3189362
# Can a neural network be used to find the best parameters of an algorithm?

(Asked by: username_0 on 2024-12-23)

I've developed a computer vision algorithm that produces a binary result from an image. This algorithm depends on a number of parameters.

Is it possible to use a neural network to learn the best parameters, given the outcome of the execution of the algorithm on several images?

**Tags:** neural-networks, computer-vision

> **Comments:**
> **username_1**: are these parameters dependent on the image you are processing or they should be something generic?  

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## 1 answers

### Answer by username_2 on 2024-12-23. Score: 0

Maybe, but it's likely overkill. In hyperparameterization, random search, successive-halving or, lastly, evolutionary optimization is generally more than enough. This is not to mention the dozen other methods people have proposed over the years.


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