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1e1a

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I read a paper a while ago (which I have failed to locate) which used around binary masks, each in front of a single photodiode, as input to a neural network, which estimated the number of people in front of this effectively ~9-pixel "camera". The binary masks and NN weights were trained at the same time. Presumably, something like this could be used to detect lack of driver focus in a far less invasive manner.

Additionally, while I don't know much about APFS, I don't think it would be beneficial to point the extracted app to blocks that are also part of the dmg file, i.e. some copying has to happen anyway.

This is fun and looks amazing, however there seems to be quite a bit of texture in the out of focus blur. There's also a lot of aliasing on the grass. Also, I think the camera shake could do with a very slight delay after the axe hits, and maybe a slightly slower decay curve.

Even worse, sometimes it dubs ads, where there's no way to switch the audio track and no way to see if it's being dubbed. This also makes it look like the dubbed audio is the original audio from the ad, which makes the advertiser look terrible.

If they can detect the faint signal of a heartbeat from so far away, why not instead deliberately transmit a weak, wider-bandwidth pseudorandom magnetic signal? Such a signal would be even harder to detect than a heartbeat without prior knowledge, yet easier to identify and track using a matched filter.