What algorithm to use
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I am stuck on what algorithm to use. I want to train my program on a dataset where i have an input image, and an output image which is a modified version of the input. The whole context of the image is important, and each pixel counts.
After training i want to input an image, and get an output similar to the training data.
supervised-learning
New contributor
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add a comment |
$begingroup$
I am stuck on what algorithm to use. I want to train my program on a dataset where i have an input image, and an output image which is a modified version of the input. The whole context of the image is important, and each pixel counts.
After training i want to input an image, and get an output similar to the training data.
supervised-learning
New contributor
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Maybe you can try autoencoders?
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– TitoOrt
2 days ago
add a comment |
$begingroup$
I am stuck on what algorithm to use. I want to train my program on a dataset where i have an input image, and an output image which is a modified version of the input. The whole context of the image is important, and each pixel counts.
After training i want to input an image, and get an output similar to the training data.
supervised-learning
New contributor
$endgroup$
I am stuck on what algorithm to use. I want to train my program on a dataset where i have an input image, and an output image which is a modified version of the input. The whole context of the image is important, and each pixel counts.
After training i want to input an image, and get an output similar to the training data.
supervised-learning
supervised-learning
New contributor
New contributor
New contributor
asked 2 days ago
Martin MMartin M
61
61
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New contributor
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Maybe you can try autoencoders?
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– TitoOrt
2 days ago
add a comment |
$begingroup$
Maybe you can try autoencoders?
$endgroup$
– TitoOrt
2 days ago
$begingroup$
Maybe you can try autoencoders?
$endgroup$
– TitoOrt
2 days ago
$begingroup$
Maybe you can try autoencoders?
$endgroup$
– TitoOrt
2 days ago
add a comment |
1 Answer
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You can use Deep convolution GAN network of Deep learning. It would be a generative model.
you can get detailed help from :
https://medium.com/@keisukeumezawa/dcgan-generate-the-images-with-deep-convolutinal-gan-55edf947c34b
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1 Answer
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1 Answer
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$begingroup$
You can use Deep convolution GAN network of Deep learning. It would be a generative model.
you can get detailed help from :
https://medium.com/@keisukeumezawa/dcgan-generate-the-images-with-deep-convolutinal-gan-55edf947c34b
New contributor
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add a comment |
$begingroup$
You can use Deep convolution GAN network of Deep learning. It would be a generative model.
you can get detailed help from :
https://medium.com/@keisukeumezawa/dcgan-generate-the-images-with-deep-convolutinal-gan-55edf947c34b
New contributor
$endgroup$
add a comment |
$begingroup$
You can use Deep convolution GAN network of Deep learning. It would be a generative model.
you can get detailed help from :
https://medium.com/@keisukeumezawa/dcgan-generate-the-images-with-deep-convolutinal-gan-55edf947c34b
New contributor
$endgroup$
You can use Deep convolution GAN network of Deep learning. It would be a generative model.
you can get detailed help from :
https://medium.com/@keisukeumezawa/dcgan-generate-the-images-with-deep-convolutinal-gan-55edf947c34b
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answered 2 days ago
ReevesReeves
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Martin M is a new contributor. Be nice, and check out our Code of Conduct.
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Maybe you can try autoencoders?
$endgroup$
– TitoOrt
2 days ago