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4 questions
-1
votes
1
answer
191
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Denoise autoencoder not training properly [closed]
I'm trying to make a denoise autoencoder wherein the encoder part is vgg16 and decoder is opposite of vgg16(encoder) network. My dataset consists of 5K images in grayscale.
Now while training, the ...
1
vote
0
answers
118
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How much data do we need for making a successful de-noising auto-encoder?
Is there a guide how much data do you need for making successful denoising model using autoencoders?
Or the rule is, the more data, the better it is?
I tried with small dataset 350 samples, to see ...
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2
votes
2
answers
2k
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How can I have the same input and output shape in an auto-encoder?
I'm building a denoising autoencoder. I want to have the same input and output shape image.
This is my architecture:
...
- 161
5
votes
1
answer
3k
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How to add a dense layer after a 2d convolutional layer in a convolutional autoencoder?
I am trying to implement a convolutional autoencoder with a dense layer at the bottleneck to do some dimensional reduction. I have seen two approaches for this, which aren't particularly scalable. The ...
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