• Facets (new session)
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• Metadata
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  • Rule: ActivityStreamsMapasEquivalentb3sb3sifpdbprdf-labelfacetshttp://dbpedia.org/resource/inference/rules/dbpedia#http://dbpedia.org/resource/inference/rules/opencyc#http://dbpedia.org/resource/inference/rules/umbel#http://dbpedia.org/resource/inference/rules/yago#http://dbpedia.org/schema/property_rules#http://www.ontologyportal.org/inference/rules/SUMO#http://www.ontologyportal.org/inference/rules/WordNet#http://www.w3.org/2002/07/owl#ldpoplwebskos-transurn:det:rdf:labelvirtrdf-labelvirtrdf-urlNone
    
  • Inverse Functional Properties: Disabled (fastest) Apply to subjects only Apply to objects only Apply to both subjects and objects
  • "Same As": Disabled (fastest) Apply to subjects only Apply to objects only Apply to both subjects and objects (recommended) Apply to subjects, objects and predicates (not recommended on big datasets) Apply to predicates only (special use cases only)

About: 80 Million Tiny Images     Goto   Sponge   NotDistinct   Permalink

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80 Million Tiny Images is a dataset intended for training machine learning systems. It contains 79,302,017 32×32 pixel color images, scaled down from images extracted from the World Wide Web in 2008 using automated web search queries on a set of 75,062 non-abstract nouns derived from WordNet. The words in the search terms were then used as labels for the images. The researchers used seven web search resources for this purpose: Altavista, Ask.com, Flickr, , Google, Picsearch and Webshots. The CIFAR-10 dataset uses a subset of the images in this dataset, but with independently generated labels.