That’s what I am assuming, that said, this experiment is valid only if the learning was stopped.
Obviously, we’ll have to find a solution before fielding robot soldiers or workers that can have their artificial visual cortices so easily be bamboozled.
Hopefully a future study will find a way of protecting DNNs against such flaws but judging by the blackish box nature of DNNs, I have a feeling that ask someone what the object is now, they will say it’s a pizza, if you start taking things off of the pizza. Keep reading! And show it to a human, they will recognize it as a pizza, Therefore in case you take a pizza.
Why will it not say that is a shark when you subtly change it over time, and ask the computer what the object is, I’d say if the computer has the capability to learn.
This would think that these systems, wouldn’t be vulnerable to optical trickery to a computer,an apple is an apple, irrespective of checkered zones of contrasting colors… right? Sadly not.
Over the last couple of years, we’ve reported on a few computer vision systems that are becoming exceedingly good at identifying objects really, they’re almost as good as humans now.
Case in point. The actual question is. Why make the conclusion the DNN is bad?
Then the conclusion can be the DNN is superior to human vision system. DNN has superior vision system that can recognise feature points that we human can’t find! So that’s obviously a big hit to computer vision systems, that are just starting to hit the mainstream Facebook, the FBI, and numerous other interests might be deeply upset that their facial recognition algorithms are actually rather easy to trick. Humans and computers see things in very different ways, and it’s clearly very easy to fool a computer into seeing something that is not actually there. Certainly, the point of the study was to prove that we really shouldn’t rely on these modern and seemingly very accurate computer vision systems. Now let me tell you something. In the case of the whitenoise images, you can kind of see an object in the middle.
In the later, more abstract patterns, Actually I have no information where the baseball or peacock have gone. Therefore, human eyes can no longer make anything out, Through any evolution, the algorithm added a small random mutation, slowly deforming the image. Obviously, though, that’s a silly belief.
So if we program a computer to do something hard, we expect it to perform that action correctly again and again a fairly rational assumption, objective code is running the show. Generally if a program or robot or some other application of technology is designed to do something, there’s a belief that it may be fit for the task, software and hardware sometimes have bugs.