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{{update|date=September 2019}}
In [[computer vision]],
Traditionally, classifiers are trained using sets of images that are labeled by hand. Collecting such a set of images is often a very time-consuming and laborious process. The use of Internet search engines to automate the process of acquiring large sets of labeled images has been described as a potential way of greatly facilitating computer vision research.<ref name = "fergus">
{{cite conference
| last = Fergus
| first = R. |author2=Fei-Fei, L. |author3=Perona, P. |author4=Zisserman, A.
| title = Learning Object Categories from Google抯 Image Search
| book-title = Proc. IEEE International Conference on Computer Vision
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|book-title = Uncertainty in Artificial Intelligence
|year = 1999
|url =
|url-status = dead
|archive-url = https://web.archive.org/web/20070710083034/http://www.cs.brown.edu/~th/papers/Hofmann-UAI99.pdf
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{{cite journal
| last = Teh
| first = Yw |author2=Jordan, MI |author3=Beal, MJ |author4=Blei, David
| title = Hierarchical Dirichlet Processes
| journal = Journal of the American Statistical Association
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{{cite conference
| last = Fergus
| first = R. |author2=Perona, P. |author3=Zisserman, A.
| title = A visual category filter for Google images
| book-title = Proc. 8th European Conf. on Computer Vision
|