
How many animals can one find in a random image? - soofy
http://community.wolfram.com/groups/-/m/t/995095
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pierrec
A more honest title would have been "Check out our animal shape generator",
though I suppose it wouldn't sound as interesting.

They touch on the cool idea of using an image identification neural network to
single out desired shapes from an arbitrarily large corpus of semi-random
generated shapes. So the way you program your random generator could determine
the style, while the identifier network would determine what will be
represented.

~~~
dalbasal
I think your linkbait detector might be evolving to work like the pareidolia
phenomenon mentioned in the article (our animal and people detectors' tendency
to produce false positives).

This might not be the best title possible, but it's not clickbait-ey, it's
just a little vague.

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czep
I'm stealing one of those to use as my avatar.

For some inexplicable reason, I find this earth-shatteringly fascinating. If
such a bewildering array of patterns can be found in random noise, maybe all
patterns -- our attempts to ascribe order to the universe -- are illusive.

~~~
maggit
This is certainly beautiful! And fascinating!

But be careful about drawing metaphysical conclusions from this. This is only
an example of selection bias. Take random noise, filter it and select examples
that probably look animal-like to humans. If the classification algorithm is
worth its salt, the selected images are bound to look interesting.

A comparison could be made to the Rorschach test; if the patient finds clear
images in the ink blot, that is supposed to say something about the patient,
not the image, because the image is by construction random.

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source99
Interestingly, Whenever I feel like my brain is firing on all cylinders I
often think I see old friends in a crowd.

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Kaibeezy
the shower of an apartment i rented long ago had old-school spatter tiles with
small random shapes remarkably similar to the ones in the article - very close
to what's in the links below, although on the ones i recall, the shapes had
smoother edges and more small white dots inside the shapes

with the hot water enveloping me in a multi-sensory white noise, i would stand
there for time=n finding faces, animals and aliens in the splotches - very zen

[http://thumbs.picclick.com/00/s/MTIwMFgxNjAw/z/9W8AAOSwmLlX5...](http://thumbs.picclick.com/00/s/MTIwMFgxNjAw/z/9W8AAOSwmLlX5~~u/$/Z-531V-1-Pc-
Vintage-Ceramic-Wall-Florida-Tile-_57.jpg)

[http://www.ebay.com/itm/Z-986-1Pc-Vintage-Ceramic-Wall-
Flori...](http://www.ebay.com/itm/Z-986-1Pc-Vintage-Ceramic-Wall-Florida-
Tile-4-3-8-Sky-Blue-Onyx-Textured-
Gloss-/351772457457?hash=item51e745b9f1:g:uVUAAOSwRQlXdbDw)

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tabeth
Can't you see anything in any image, given any interpretation?

~~~
ovi256
Sure, but the most interesting interpretations are usually based on aprioris
learned in this universe.

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ttoinou
Awesome ! I also see a lot of living creatures in flames (try to take pictures
with a DSLR during 1/2000 second ;) ), including phoenixes, seehorses and
riders.

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rabboRubble
No animal shapes are directly visible.

~~~
user837387
I see plenty or rabbits and few birds. I'm sure I could find more if cared to
spend more time on this.

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tantalor
Satire?

~~~
SomeStupidPoint
Why would it be satire?

The question of pattern recognition in random noise is interesting and a
legitimate question. Animals (given our propensity to see then) and an
interesting subject matter.

~~~
jlarocco
Generating random noise and then filtering it to "find" patterns seems
dubious, at best. Why not just generate animal shapes in the first place?

Starting from a random image it's possible to manipulate and filter it to find
literally anything. It doesn't mean there are "animal pictures" in the random
data; it means the image has been manipulated to look like it. It's a
tautology.

~~~
SomeStupidPoint
In a sufficiently large random image, you'll (probably) find as detailed of a
picture of a rabbit as you like.

The question is about how often image recognition (either human or
algorithmic) picks up a signal in random noise -- that is, how often we see
things that aren't there (or if you prefer, _are_ there, but by chance). Of
course you _can_ find anything, the question is with what frequency.

If you've ever spent much time looking at random patterns, you'd know that
we're prone to seeing things that aren't there in noise. Modeling that
phenomenon is interesting (at least to me).

