This is the same as the entry on the wishlist for 2016, but describes the
actual method.
https://meta.wikimedia.org/wiki/2016_Community_Wishlist_Survey/Categories/Commons#Use_computer_vision_to_propose_categories

Both contrastive and triplet loss can be used while learning, but neither
are described at Wikipedia.

On Sun, Jan 14, 2018 at 8:16 PM, Pine W <wiki.p...@gmail.com> wrote:

> Hi John,
>
> I have not heard of an initiative to use Siamese neural networks for image
> classifications on on Commons. You might make a suggestion on the AI,
> Research, and/or Commons mailing lists regarding this idea. You might also
> make a suggestion in IdeaLab
> <https://meta.wikimedia.org/wiki/Grants:IdeaLab>.
>
> Pine <https://meta.wikimedia.org/wiki/User:Pine>
> <https://en.wikipedia.org/wiki/User:CatherineMunro/Bright_Places>
>
> On Sun, Jan 14, 2018 at 3:46 AM, John Erling Blad <jeb...@gmail.com>
> wrote:
>
> > Has anyone tried to use a Siamese neural network for image classification
> > at Commons? I don't know if it will be good enough to run in autonomous
> > mode, but it will probably be a huge help for those that do manual
> > classification.
> >
> > Imagine a network providing a list of possible categories, and the user
> > just ticks off usable categories.
> >
> > A Siamese network can be learned by using a triplet loss function, where
> > the anchor and the positive candidate comes from the same category, and
> the
> > negative candidate comes from an other category but are otherwise close
> to
> > the anchor.
> >
> > Output from the network is like a fingerprint, and those fingerprints can
> > be compared to other images with known fingerprints, or against a
> > generalized fingerprint for a category.
> >
> > John Erling Blad
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