New answers tagged convolutional-neural-networks
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Do GANs have constant running time?
The question is a bit ill defined... usually when we want some bound on the running time, we have to say with respect to what
For example:
sorting is O(nlogn) wrt the size of the input
Transformer is ...
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Encoder-Decoder Semantic Segmentation
There is never a 100% accurate theory, however it's been observed to be beneficial, however I would argue that is due to the following:
you want to have a latent dimension, to learn the manifold ...
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The training process of a conditional GAN
I assume you mean how to label the image and class inputs since the discriminator can reasonably output either "real" or "fake" labels for either of those inputs, and you generally ...
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Is it possible to build a convolutional autoencoder with fully connected bottleneck with low dimension?
In general, very simple datasets like MNIST and Fashion-MNIST can be encoded in just two dimensions, without sacrificing too much reconstruction quality.
For more complex data, this is often neither ...
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In the conditional GAN (cGAN) architecture, why does the discriminator need conditional variable?
Because otherwise there is no conditioning... consider the case where you condition the generator but not the discriminator: given an image and a label, the generator proposes an image, which will be ...
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Generator loss not decreasing while training GAN
Without looking too much at the code, as this is not a place to ask debugging questions, I'll give some advice on how to potentially solve your problems. I'll assume your code is operational (its ...
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Super Resolution CNN generates black dots on output images
Great that a solution was found (clamp larger-than-one pixels' brightness before showing the image). But I suggest that you either add a sigmoid activation, or clamp the network's output directly from ...
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