When using neural networks to detect features in an image, how can locate that specific feature in the original image?
What is an appropriate size for a latent space of (variational) autoencoders and how it varies with the features of the images?
Why would neural network dream scenes mirror the hallucinations people experience when they're tripping?
Is it feasible to train a Machine Learning Model (with image inputs) in an average personal computer?
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