I am new to image classification and hope to set up a model which will classify large images (I am using R keras). Each image will represent a 10m by 10m square with pixels representing 1 cm. I need the fine resolution to capture the detail in the images. I can follow and run the keras examples for "regular" images with less pixels, like the MNIST data or images of cars or fruits. However, I don't have my real data yet so I am unsure what will happen if I attempt to use images with 1M pixels.
My question is:
- Is it possible to use images this large?
- If so, are there any special considerations I need to take into account or special processing that would be required?
- Where is a good place to start?