AI's capabilities are limited. They can with great accuracy identify leaf types. A specialist could work onward from that. Consider this applied to completely uncategorized images.
Mind you I am at a phase of proposing a task for ImageClef which is why I have asked about this here. Examples I mentioned are to give an idea about the capability of the current state of ImageClef contributors. What would community want more as a goal of automated tagging? -- とある白い猫 (To Aru Shiroi Neko) On Mon, Sep 26, 2011 at 19:32, Andre Engels <[email protected]> wrote: > On Mon, Sep 26, 2011 at 6:43 PM, Paul Houle <[email protected]> wrote: > >> ** >> I've made some attempt to map images on Wikimedia commons to >> distinct concepts from DBpedia, see >> >> http://ookaboo.com/ >> >> This could be useful for forming a training set, but I haven't yet >> got around to releasing a public dump of the data. I have about 1 million >> things classified and could certainly extend the strategies used to get >> more. >> >> Unless there's been a really unprecedented breakthrough, I'd think >> that the application of machine vision to Wikimedia faces the problem of >> getting enough training data. If you had thousands or tens of thousands of >> photos that were labeled 'cat' or 'not cat', or 'member of plant species X' >> or 'not member of plant species X', you can train a classifier to make the >> distinction. However, if you've got two or three bad photos of a >> particular plant (which is what you have most of the times in Commons) you >> don't have enough training data to generalize. >> >> If you've got a specific mission, say genitals recognition, I think >> you can make progress, but to attack the general problem you need to go big >> with your training sets. >> > > Every small category is a part of a big category. A system such as this > will not be able to specify plant species, but it might well be able to find > pictures of plants. If it then gives a list of plant pictures that are not > in some plant category, animal pictures that are not in animal category, > buildings that are not in a regional building category, maps that are not in > a map of category, paintings that are not in a painter category, famous > people that are not in a people category etcetera, it could deliver those to > volunteers to further classify. > > -- > André Engels, [email protected] > > > _______________________________________________ > Commons-l mailing list > [email protected] > https://lists.wikimedia.org/mailman/listinfo/commons-l > >
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