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Comment by GotAnyMegadeth | Hacker News Reader

When we can get computers to tell the difference between animals accurately we can make a real life pokedex app. I can't wait.

EDIT: If anyone one thinks we can start working on this now, I'm game.

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Not quite a pokedex, but you can get a leaf-dex today!

http://leafsnap.com

You can take photos of leaves and it'll identify them for you :)

Oh my god you're right, wow, I need to start working on this now and fulfill my dream to be the very best...

EDIT: I would definitely be interested in building something like this. iOS/mobile app? I have basic experience in ML and have written an ANN in C++ to classify letters (they were 'pixelated' images, 1 and 0's).

If I saw this post earlier maybe I would taken more AI route with my classes.

Ha! If I hadn't thought ML was a fad used for making book recommendations on Amazon I wouldn't be sitting here kicking myself for never learning AI/ML techniques.

Bloody ML Summer...

http://www.umiacs.umd.edu/~kanazawa/papers/eccv2012_dog_fina...

http://www.icsi.berkeley.edu/~farrell/birdlets

Note that these are both approaches to do "fine-scaled visual categorization" (FGVC), which assumes you already know you're looking at a dog/bird and want to identify which species it is. This is increasingly becoming an important problem in computer vision, and in fact we just recently held the 2nd FGVC workshop [1] this year to encourage more people to work on these sorts of things.

The kaggle competition is for determining if it is a dog or cat, so it's a bit unlikely that one of these approaches would directly work (although they might be adaptable to the task). See my other comment [2] for a lighter-weight approach that is likely to do just as well, if not better.

[1] http://www.fgvc.org/

[2] https://news.ycombinator.com/item?id=6446309

It's actually already possible to train convolutional network-like models to distinguish between a variety of dogs, cats etc with precision that is pretty much super human. The real problem is getting high-quality training data without involving tons of domain experts that would tells us with high degree of confidence whether a given image is of a specific breed of dog (getting millions of images of dogs is easy, so is building a classifier).

It's not immediately obvious to me how useful such an app would be btw. Unless I of course misunderstood what a "real life pokedex app" is :).

If you can figure out the enemy dog is a fire type, you can switch your team up accordingly :)

Is state-of-the art for that kind of recognition deep learning?

Yes, though I think on public benchmarks this is still not the case. There's a dog-breed classification problem in this year's Fine-Grained challenge (https://sites.google.com/site/fgcomp2013/) so we'll see in December!

This would actually be kind of amazing.

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