4 ms·
I think it's more than just estimating the count of objects. We also "approximate" for example a spatial distribution - think about how when running through ro
by kontorlaore 7y ago
I think it's more than just estimating the count of objects.
We also "approximate" for example a spatial distribution - think about how when running through rough terrain, you instantly know which path to choose to encounter fewer rocks. You are certainly not focusing and counting each individual rock.
- Mirioron 7y agoThe image in the article is really an example of a spatial distribution and fits very well. There's really no way to count which color there is more of in some area of the image, but you can still estimate which one there is more of. I'm not even sure how we could numerically assess that without guesstimation.
- emilfihlman 7y agoEh? That is one of the easiest things you can do with parallel/analog/fpga computing. You simply sum (and this does not mean compute summing, it just happens) the signals that respond in a certain way. It doesn't require much.
- Mirioron 7y agoSure, with computing, but if you didn't have access to such technology?
- emilfihlman 7y agoI mean, just looking at our eyes: it's a field of evenly spaced measurement devices that send a direct signal to out brain. Ie we have a "parallel transmission of pixels". You then just check what colour has the strongest (most) signals. Or do you mean something else? Like how to do that consciously or something and not like, how it's possible?
- jimktrains2 7y agoOur rods and cones are no where near uniformly distributed, even after accounting for the blood vessel running around the retina.
- emilfihlman 7y agoIf so, just add another layer that biases the result based on actual distribution.
- deleted 7y ago[deleted]