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Convolutional neural network: Difference between revisions
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though they can be used anywhere you have a rectangular grid with spatial relationship among your data. | though they can be used anywhere you have a rectangular grid with spatial relationship among your data. | ||
==Motivation== | |||
[https://arxiv.org/pdf/1611.08097.pdf Geometric Deep Learning]<br> | |||
Convolutional neural networks leverage the following properties of images: | |||
* ''Stationarity'' or shift-invariance - objects in an image should be recognized regardless of their position | |||
* ''Locality'' or local-connectivity - nearby pixels are more relevant than distant pixels | |||
* ''Compositionality'' - objects in images have a multi-resolution structure. | |||
==Convolutions== | ==Convolutions== | ||