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> CNNs can be used to categorize other types of data too. The trick is, whatever data type you start with, to transform it to make it look like an image. This
by j1vms 10y ago
> CNNs can be used to categorize other types of data too. The trick is, whatever data type you start with, to transform it to make it look like an image.
This is an interesting point, and I assume that 'make it look look like an image' means the same thing as 'think of it as an image'. Can others here who works with CNNs regularly or professionally, comment on whether the author's intuition is essentially correct (give or take some details of course)?
- sprobertson 10y agoOne thing that might work well with a CNN is geospatial data (easy to consider as an image).
- arketyp 10y agoIt comes down to the characterizing architecture of convolutional nets, that is weight sharing, and the assumption on data this makes. If by image one means something where you can expect any pattern (at some level in the hierarchy) being equally likely to occur anywhere across an input dimension, then yes this is true. Personally I would say that this is too narrow of a definition of an image (too great of an assumption), and, interestingly enough, perhaps too broad too. I am not a pro. [Edit] Too broad in the sense that, intuitively, there is perhaps an implied assumption of continuity of the input function defining the image. Note that such assumptions can be made explicit with various so-called statistical priors incorporated in the network.