

Deep Learning Image Classifier - adid
http://deeplearning.cs.toronto.edu/

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4qbomb
LOL! [http://i.imgur.com/Xs3GrGk.png](http://i.imgur.com/Xs3GrGk.png)

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rfrey
Not too bad! It was low probability, but it did somehow recognize Mike.

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bhouston
Didn't give me results at all to the three images I uploaded. Might be broken.

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dkhar
It looks like that's the case -- none of the example images on the front page
work for me.

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blobbers
Same for me. Tried safari and chrome.

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joyofdata
President Obama is recognized either as ...

... a mountain-bike / all-terrain-bike
([http://cdn2.spiegel.de/images/image-730849-galleryV9-vuuv.jp...](http://cdn2.spiegel.de/images/image-730849-galleryV9-vuuv.jpg))

... or a rugby ball
([http://cdn2.spiegel.de/images/image-730849-breitwandaufmache...](http://cdn2.spiegel.de/images/image-730849-breitwandaufmacher-
vuuv.jpg))

... or a bullet proof vest ([http://cdn2.spiegel.de/images/image-730849-thumb-
vuuv.jpg](http://cdn2.spiegel.de/images/image-730849-thumb-vuuv.jpg))

I guess the implementation leaves room for improvement :)

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phrixus
There are several of these image classifiers now that someone should run an
accuracy/speed/price comparison between

AlchemyAPI:
[http://www.alchemyapi.com/products/demo/alchemyvision/](http://www.alchemyapi.com/products/demo/alchemyvision/)

UToronto

Rekognition:
[http://rekognition.com/demo/concept](http://rekognition.com/demo/concept)

Clarifai: [http://www.clarifai.com/](http://www.clarifai.com/)

I'm doing it myself, but I have a conflict of interest

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sullivak
Well there is the ImageNet challenge [http://www.image-
net.org/challenges/LSVRC/2013/results.php](http://www.image-
net.org/challenges/LSVRC/2013/results.php) I'm not sure if Alchemy or
Rekognition maps to any of those teams though.

~~~
Houshalter
Also see
[https://rodrigob.github.io/are_we_there_yet/build/classifica...](https://rodrigob.github.io/are_we_there_yet/build/classification_datasets_results.html)

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tly_alex
[http://rekognition.com/demo/concept](http://rekognition.com/demo/concept)

Rekognition API has a similar API for all developers free.

It's reliable and very fast.

Checkout their demo page.

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im3w1l
I only tried one (hard) image, pizza-, sandwich- bloody mary
[https://imgur.com/30OgNdd](https://imgur.com/30OgNdd). Rekognition seems to
be working better than submission

Rekognition:

7.55% fruit; 0.92% dinner; 0.88% produce; 0.87% alcohol; 0.84% sliced

Toronto:

50% American lobster, Northern lobster; 12% plate; 7% crayfish, crawfish,
crawdad; 7% Dungeness crab, Cancer magister; 4% king crab, Alaska crab; 4%
butcher shop, meat market; 4% grocery store, grocery; 4% pomegranate

I find this interesting because I thought Hinton's group had state of the art
tech. Who are these people and how do they do it?

~~~
mraison
I think that when you're not expected to publish any papers to rationalize
what you're doing, you're free to use any possible ugly hack to improve your
results, (using a "kitchen sink" approach where you just combine the results
of lots of unrelated techniques, extracting words from the URL, using the URL
to actually fetch some related textual content on the website, etc). This
gives private companies a competitive advantage over research institutions -
their only purpose is to "make things work", not to introduce new techniques
and have interesting insight about them.

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kephra
tried two images:

[http://kephra.de/Dampf/IMG_20140620_133839_800x600.jpg](http://kephra.de/Dampf/IMG_20140620_133839_800x600.jpg)
<\- an ecigarette, and the classifier thought its a fountain pen. Well thats
not bad, I got this joke/question from humans also.

[http://kephra.de/pix/Snoopy/thump/IMG_20130822_135928_640x48...](http://kephra.de/pix/Snoopy/thump/IMG_20130822_135928_640x480.jpg)
<\- here it thought its a speed boat ... well my boat is fast, but not a
speedboat, but an sailing boat. It offered several more boat types, but not
just a plain sailing boat. Interesting here is that the last suggestion of
only 1% could be considered right as "dock, dockage, docking facility"

Tried some other images from the lifestyle section of my homepage, but it
looks as if the system newer saw a sewing machine before as it gives "Low
recognition confidence", and no tags.

~~~
Estragon
I can see how it could get speedboat from the shape of the hull.

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frobozz
It seems strange that they would include in their set of example images, a
picture of the most famous mausoleum in the world, without it being tagged
with mausoleum or tomb or anything like that.

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PanMan
And it is tagged 99% mosque, while it isn't one. (the building on the left of
it, not in the image, is).

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frobozz
If I uploaded my own picture of the Taj Mahal and it told me it was a Mosque,
I wouldn't be surprised, and I'd probably be reasonably impressed. The dome
and minarets do rather give that impression, and I wouldn't really expect a
computer to be able to tell the difference.

The reason I find it odd is that I would expect the first example on a demo to
be carefully chosen to show off the system in the best light. It would be one
that has perfect or near-perfect tagging. Maybe later on, I would show the
shortcomings with a tricky image like this.

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3rd3
Are there actually any image feature detectors and descriptors involved (like
blob, edge and texture detectors) or is this solely based on artificial neural
networks?

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sjtrny
Interestingly it has been shown that the result from some neural networks is
equivalent to using classification with some predefined filters. These filters
could be considered as a feature descriptor. See this talk from CVPR
[http://techtalks.tv/talks/plenary-talk-are-deep-networks-
a-s...](http://techtalks.tv/talks/plenary-talk-are-deep-networks-a-solution-
to-curse-of-dimensionality/60315/).

~~~
chestervonwinch
Thanks for sharing this. I enjoy Mallat's point of view. He has some similar
talks on videolectures.net for anyone who's interested.

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mrfusion
What data was it trained on?

Also can it tell you where in the image the identified object is?

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miket
This was pre-trained on ImageNet classes. You can find more information here:
[http://www.image-net.org](http://www.image-net.org)

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raverbashing
My results (yeah, a tough image)
[http://imgur.com/pbH52xW](http://imgur.com/pbH52xW)

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Crito
From my experience with cats, "doormat" is actually pretty accurate. Damn
things always dart right under my feet.

