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I'm working on a convolutional neural network and I've found various methods of building filters to convolve the image with. What are the advantages and disadvantages of each?

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In some cases, autoencoders may enhance your performance, produce biologically plausible filters, and more importantly, give you a model based on your data instead of predefined filters. Autoencoders provide you a filter that may fit your data better, in general. The only downside is, of course, the additional computation time. However, in many cases, it doesn't hinder you from learning online.

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