{"id":"https://openalex.org/W2188365053","doi":null,"title":"Learning Object Categories From Internet Image Searches This paper shows how the results returned by an image search engine can be used to construct models from Internet images and use them for object recognition.","display_name":"Learning Object Categories From Internet Image Searches This paper shows how the results returned by an image search engine can be used to construct models from Internet images and use them for object recognition.","publication_year":2010,"publication_date":"2010-01-01","ids":{"openalex":"https://openalex.org/W2188365053","mag":"2188365053"},"language":"en","primary_location":{"id":"mag:2188365053","doi":null,"is_oa":false,"landing_page_url":"https://cs.stanford.edu/groups/vision/pdf/FergusFei-FeiPeronaZisserman2010.pdf","pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":null},"volume":null,"type":"article","indexed_in":[],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5089960673","display_name":"Rob Fergus","orcid":"https://orcid.org/0009-0005-3077-2495","observed_orcids":["https://orcid.org/0009-0005-3077-2495"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Rob Fergus","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5026825380","display_name":"Pietro Perona","orcid":"https://orcid.org/0000-0002-7583-5809","observed_orcids":["https://orcid.org/0000-0002-7583-5809"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Pietro Perona","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0002-7583-5809","affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5057678172","display_name":"Andrew Zisserman","orcid":"https://orcid.org/0000-0002-8945-8573","observed_orcids":["https://orcid.org/0000-0002-8945-8573"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Andrew Zisserman","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0002-8945-8573","affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.2074936,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.8119999766349792,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.8119999766349792,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.15760000050067902,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.01209999993443489,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/object-category-learning","display_name":"object category learning","score":0.8399999737739563},{"id":"https://openalex.org/keywords/image-search-engines","display_name":"image search engines","score":0.7839999794960022},{"id":"https://openalex.org/keywords/object-recognition","display_name":"object recognition","score":0.5809999704360962},{"id":"https://openalex.org/keywords/probabilistic-latent-semantic-analysis","display_name":"probabilistic latent semantic analysis","score":0.9089999794960022}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7832058668136597},{"id":"https://openalex.org/C110875604","wikidata":"https://www.wikidata.org/wiki/Q75","display_name":"The Internet","level":2,"score":0.6831516027450562},{"id":"https://openalex.org/C112933361","wikidata":"https://www.wikidata.org/wiki/Q2845258","display_name":"Probabilistic latent semantic analysis","level":2,"score":0.6570623517036438},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.6388185620307922},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.6233607530593872},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.5393381714820862},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5175415873527527},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4654216468334198},{"id":"https://openalex.org/C97854310","wikidata":"https://www.wikidata.org/wiki/Q19541","display_name":"Search engine","level":2,"score":0.4386022686958313},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3822844624519348},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.33029165863990784},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.20690172910690308},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"mag:2188365053","doi":null,"is_oa":false,"landing_page_url":"https://cs.stanford.edu/groups/vision/pdf/FergusFei-FeiPeronaZisserman2010.pdf","pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":37,"referenced_works":["https://openalex.org/W128019999","https://openalex.org/W1496659369","https://openalex.org/W1576445103","https://openalex.org/W1589362500","https://openalex.org/W1625255723","https://openalex.org/W1699734612","https://openalex.org/W1739260168","https://openalex.org/W1880262756","https://openalex.org/W1987496434","https://openalex.org/W2027444427","https://openalex.org/W2080289064","https://openalex.org/W2107034620","https://openalex.org/W2107743791","https://openalex.org/W2110717342","https://openalex.org/W2111861094","https://openalex.org/W2115733720","https://openalex.org/W2118509786","https://openalex.org/W2119747362","https://openalex.org/W2123053055","https://openalex.org/W2124386111","https://openalex.org/W2128197086","https://openalex.org/W2131846894","https://openalex.org/W2134557905","https://openalex.org/W2137471889","https://openalex.org/W2149489787","https://openalex.org/W2154301842","https://openalex.org/W2154422044","https://openalex.org/W2162820221","https://openalex.org/W2162915993","https://openalex.org/W2164598857","https://openalex.org/W2164877691","https://openalex.org/W2167090521","https://openalex.org/W2168002178","https://openalex.org/W2171188998","https://openalex.org/W2171706135","https://openalex.org/W2172191903","https://openalex.org/W2217896605"],"related_works":["https://openalex.org/W2027444427","https://openalex.org/W7100036676","https://openalex.org/W2172191903","https://openalex.org/W7053503548","https://openalex.org/W34450652","https://openalex.org/W2347090428","https://openalex.org/W2992525561","https://openalex.org/W2114921175","https://openalex.org/W1578226009","https://openalex.org/W2160802195"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"we":[3,61],"describe":[4,88],"a":[5,26,34,46],"simple":[6,90],"approach":[7],"to":[8,39,51,65,109,126,145],"learning":[9,82],"models":[10,56,85,113],"of":[11,81,121,139],"visual":[12],"object":[13,83,112],"categories":[14],"from":[15,18,49,58,93,114],"images":[16,24,129],"gathered":[17],"Internet":[19,59],"image":[20,150],"search":[21,133,141],"engines.":[22],"The":[23],"for":[25,101],"given":[27],"keyword":[28],"are":[29],"typically":[30],"highly":[31],"variable,":[32],"with":[33],"large":[35],"fraction":[36],"being":[37],"unrelated":[38],"the":[40,63,79,94,122,128,132,137,140],"query":[41],"term,":[42],"and":[43,143],"thus":[44,135],"pose":[45],"challenging":[47],"environment":[48],"which":[50],"learn.":[52],"By":[53],"training":[54,68],"our":[55],"directly":[57],"images,":[60],"remove":[62],"need":[64],"laboriously":[66],"compile":[67],"data":[69,151],"sets,":[70],"required":[71],"by":[72,131],"most":[73],"other":[74,149],"recognition":[75],"approachesVthis":[76],"opens":[77],"up":[78],"possibility":[80],"category":[84],"''on-the-fly.''":[86],"We":[87,117],"two":[89,119],"approaches,":[91],"derived":[92],"probabilistic":[95],"latent":[96],"semantic":[97],"analysis":[98],"(pLSA)":[99],"technique":[100],"text":[102],"document":[103],"analysis,":[104],"that":[105],"can":[106],"be":[107],"used":[108],"automatically":[110],"learn":[111],"these":[115],"data.":[116],"show":[118],"applications":[120],"learned":[123],"model:":[124],"first,":[125],"rerank":[127],"returned":[130],"engine,":[134],"improving":[136],"quality":[138],"engine;":[142],"second,":[144],"recognize":[146],"objects":[147],"in":[148],"sets.":[152]},"counts_by_year":[],"updated_date":"2026-10-07T09:51:55.459714","created_date":"2016-06-24T00:00:00"}