Questions tagged [transpose-convolution]

7 questions
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How will the filter size affect the transpose convolution operation?

After a series of convolutions, I am up-sampling a compressed representation, I was curious what is the methodology I should follow to choose an optimum kernel size for up-sampling. How will the filter (or kernel) size affect the transpose…
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Visualization of Transposed Convolutions

After reading on Transposed Convolutions and Fully Convolutional Networks in the d2l book (14.10 and 14.11), I wondered about the visualization of transposed convolutions. As you probably know, randomly initialized convolutional kernels learn to…
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CFD Reinforcement Learning Topology optimization wind tunnel

I want to create a reinforcement learning environment, designed for win tunnel simulations, where for each iteration a deep convolutional model could receive the 3D vector/scalar fields from the past simulation and output a better shape that…
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Concrete example of how transposed convolutions are able to *add* features to an image

Say we have a simple gray scale image. If we use a filter which is just the 3x3 identity matrix (or more pointedly the identity matrix but with -1 instead of the 0 entries), it is fairly easy to see how applying this filter with stride length 1 and…
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Transpose convolution in TiF-GAN: How does "same" padding works?

This question should be quite generic but I faced the problem in the case of the TiF-GAN generator so I am going to use it as an example. (Link to paper) If you check the penultimate page in the paper you can find the architecture design of the…
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Is a Conv2DTranspose the same as a full convolution?

I am currently creating a GAN model from scratch (following this tutorial: https://machinelearningmastery.com/how-to-develop-a-generative-adversarial-network-for-an-mnist-handwritten-digits-from-scratch-in-keras/) but I can't find out how to…
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Studying the speech-generation model and have question about the confusing nature of model input and outputs

I am currently studying this model speech generation known as WaveNet model by Google using the linked original paper and this implementation. I find the model very confusing in the input it takes and the output it generates, and some of the layer…