Best way to approach multiband imagery w/ transfer learning?

Hey everyone,

Thinking about this in relation to satellite imagery, but probably also applies to medical imagery.

Size/memory issues aside, was wondering how people have/would take advantage of the multispectral bands associated with satellite imagery for successful transfer learning on something not-so-similar such as an imagenet pretrained model.

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