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Neural networks are very much real-time. They generally consist of a fixed series of math operations of fixed size. Only the weights and inputs change.

The neural net will never be late. It just might be inaccurate.



Huh, I suppose they aren't inherently incompatible with real-time constraints. It looks like it's pretty challenging to do in practice though.

I'm still somewhat confused as to how multi-object recognition works in a real-time way, naively I'd presume that recognizing n+1 objects in a frame would take longer than n objects.

You might be able to more practically get real-time neural networks using something like YOLO (you only look once)?

Either way it seems to me like hard real-time neural networks are a very challenging problem.




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