https://hackaday.com/2014/04/05/taking-pictures-with-a-dram-...
Another interesting thing is that for training neural networks for image recognition purpose information about location of individual pixels is not necessary at all.
Any idea why this happens?
> Exposing the capacitor to light causes it to discharge faster.
Capacitors on DRAMs are usually implemented as PN junctions, maybe even parasitic capacitance of a transistor is used. Photons hitting depletion region of PN junction decreasing it hence increasing conductivity.
I know CCDs for astrophotography have large photosites to increase the signal/noise ratio. It seems like this array would have the same qualities.
Do you know what the dynamic range is, how many stops the sensor can capture?
This is really interesting, so I'd really like to see a write-up instead of just a video.
https://www.sentex.ca/~mwandel/tech/scanner.html
This isn't exactly what you're looking for, but you run into some of the same limitations using a scanner as a large format back: moving objects end up distorted by the movement of the scanner "head" as it scans the image plane.
I scavenged a dozen of heads to make a giant wall scanning bar.
These should be a good fit for the needed image circle and give better images as well.
Convolutions use the spatial information. I'm less sure whether attention-based approaches typically use it.