I'm new in this argument, my question is:
Can convolution be applied in other contexts different from image recognition? Is there a good source to learn from?
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Yes, Convolutional Neural Networks(CNNs) can and have been applied to non-image problems. Arguably, any problem in which the location of a feature(s) is relevant can be attempted via CNNs. CNNs works under the assumption that points close to each other in the data share some correlations/relationship whist points further apart don't share as much information. So, theoretically, if you can phrase your problem so that it meets this requirement(s), it can be attempted by a convolutional neural network. Here are few applications of CNNss that are dont involve images:
I've used 1-D CNNs on spectral data. Here are some examples of CNNs applied to spectral data :
CNNs are generally designed for 2D (generally image) data. Hence, other usages are most likely a "hack" to CNN logic.
You can check how to extract features and classify texts with CNN through here.