{"id":"https://openalex.org/W2144269124","doi":"https://doi.org/10.1109/cvpr.2009.5206582","title":"Learning query-dependent prefilters for scalable image retrieval","display_name":"Learning query-dependent prefilters for scalable image retrieval","publication_year":2009,"publication_date":"2009-06-01","ids":{"openalex":"https://openalex.org/W2144269124","doi":"https://doi.org/10.1109/cvpr.2009.5206582","mag":"2144269124"},"language":"en","primary_location":{"id":"doi:10.1109/cvpr.2009.5206582","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr.2009.5206582","pdf_url":null,"source":{"id":"https://openalex.org/S4363607795","display_name":"2009 IEEE Conference on Computer Vision and Pattern Recognition","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2009 IEEE Conference on Computer Vision and Pattern Recognition","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"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/A5082736347","display_name":"Lorenzo Torresani","orcid":null},"institutions":[{"id":"https://openalex.org/I107672454","display_name":"Dartmouth College","ror":"https://ror.org/049s0rh22","country_code":"US","type":"education","lineage":["https://openalex.org/I107672454"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Lorenzo Torresani","raw_affiliation_strings":["Dartmouth College, Hanover, NH, USA","Dartmouth College, Hanover NH, USA"],"affiliations":[{"raw_affiliation_string":"Dartmouth College, Hanover, NH, USA","institution_ids":["https://openalex.org/I107672454"]},{"raw_affiliation_string":"Dartmouth College, Hanover NH, USA","institution_ids":["https://openalex.org/I107672454"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5043531170","display_name":"Martin Szummer","orcid":null},"institutions":[{"id":"https://openalex.org/I1290206253","display_name":"Microsoft (United States)","ror":"https://ror.org/00d0nc645","country_code":"US","type":"company","lineage":["https://openalex.org/I1290206253"]},{"id":"https://openalex.org/I4210164937","display_name":"Microsoft Research (United Kingdom)","ror":"https://ror.org/05k87vq12","country_code":"GB","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210164937"]}],"countries":["GB","US"],"is_corresponding":false,"raw_author_name":"Martin Szummer","raw_affiliation_strings":["Microsoft Research Limited, Cambridge, UK","Microsoft Research, Cambridge, UK;"],"affiliations":[{"raw_affiliation_string":"Microsoft Research Limited, Cambridge, UK","institution_ids":["https://openalex.org/I4210164937"]},{"raw_affiliation_string":"Microsoft Research, Cambridge, UK;","institution_ids":["https://openalex.org/I1290206253"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5018851970","display_name":"Andrew Fitzgibbon","orcid":"https://orcid.org/0000-0002-9839-660X"},"institutions":[{"id":"https://openalex.org/I4210164937","display_name":"Microsoft Research (United Kingdom)","ror":"https://ror.org/05k87vq12","country_code":"GB","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210164937"]},{"id":"https://openalex.org/I1290206253","display_name":"Microsoft (United States)","ror":"https://ror.org/00d0nc645","country_code":"US","type":"company","lineage":["https://openalex.org/I1290206253"]}],"countries":["GB","US"],"is_corresponding":false,"raw_author_name":"Andrew Fitzgibbon","raw_affiliation_strings":["Microsoft Research Limited, Cambridge, UK","Microsoft Research, Cambridge, UK;"],"affiliations":[{"raw_affiliation_string":"Microsoft Research Limited, Cambridge, UK","institution_ids":["https://openalex.org/I4210164937"]},{"raw_affiliation_string":"Microsoft Research, Cambridge, UK;","institution_ids":["https://openalex.org/I1290206253"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5082736347"],"corresponding_institution_ids":["https://openalex.org/I107672454"],"apc_list":null,"apc_paid":null,"fwci":1.6174,"has_fulltext":false,"cited_by_count":28,"citation_normalized_percentile":{"value":0.86116098,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"3","issue":null,"first_page":"2615","last_page":"2622"},"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":0.9998000264167786,"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":0.9998000264167786,"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":0.9994999766349792,"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/T11269","display_name":"Algorithms and Data Compression","score":0.9861000180244446,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/computer-science","display_name":"Computer science","score":0.7681682705879211},{"id":"https://openalex.org/keywords/image-retrieval","display_name":"Image retrieval","score":0.6484689712524414},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.48439961671829224},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.43604668974876404},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.42990708351135254},{"id":"https://openalex.org/keywords/query-expansion","display_name":"Query expansion","score":0.42934364080429077},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4229435622692108},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.37050095200538635},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.08671548962593079}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7681682705879211},{"id":"https://openalex.org/C1667742","wikidata":"https://www.wikidata.org/wiki/Q10927554","display_name":"Image retrieval","level":3,"score":0.6484689712524414},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.48439961671829224},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.43604668974876404},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.42990708351135254},{"id":"https://openalex.org/C99016210","wikidata":"https://www.wikidata.org/wiki/Q5488129","display_name":"Query expansion","level":2,"score":0.42934364080429077},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4229435622692108},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.37050095200538635},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.08671548962593079}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/cvpr.2009.5206582","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr.2009.5206582","pdf_url":null,"source":{"id":"https://openalex.org/S4363607795","display_name":"2009 IEEE Conference on Computer Vision and Pattern Recognition","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2009 IEEE Conference on Computer Vision and Pattern Recognition","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.153.2391","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.153.2391","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://research.microsoft.com/pubs/81353/TorresaniSzummerFitzgibbon-learning-query-cvpr09.pdf","raw_type":"text"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.415.5657","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.415.5657","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.cs.dartmouth.edu/~lorenzo/Papers/tsf-cvpr09.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Quality Education","score":0.47999998927116394,"id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":33,"referenced_works":["https://openalex.org/W123402803","https://openalex.org/W1492353517","https://openalex.org/W1531520279","https://openalex.org/W1532325895","https://openalex.org/W1556531089","https://openalex.org/W1576445103","https://openalex.org/W2055906546","https://openalex.org/W2101098151","https://openalex.org/W2119996767","https://openalex.org/W2125203709","https://openalex.org/W2128017662","https://openalex.org/W2139882995","https://openalex.org/W2141362318","https://openalex.org/W2149991777","https://openalex.org/W2151103935","https://openalex.org/W2155979701","https://openalex.org/W2160978182","https://openalex.org/W2162881463","https://openalex.org/W2170146448","https://openalex.org/W2170708028","https://openalex.org/W2172188317","https://openalex.org/W2172232203","https://openalex.org/W2435338979","https://openalex.org/W3005890292","https://openalex.org/W4213009331","https://openalex.org/W6604887717","https://openalex.org/W6633472159","https://openalex.org/W6634343353","https://openalex.org/W6674896937","https://openalex.org/W6680676027","https://openalex.org/W6684997022","https://openalex.org/W6718488237","https://openalex.org/W7062670285"],"related_works":["https://openalex.org/W2389214306","https://openalex.org/W4235240664","https://openalex.org/W2965083567","https://openalex.org/W1838576100","https://openalex.org/W2095886385","https://openalex.org/W2560191017","https://openalex.org/W2889616422","https://openalex.org/W2089704382","https://openalex.org/W1983399550","https://openalex.org/W97075385"],"abstract_inverted_index":{"We":[0,48,113],"describe":[1],"an":[2,108,117,133],"algorithm":[3],"for":[4,13,120,132],"similar-image":[5],"search":[6,80,85],"which":[7,33,128],"is":[8,26,173],"designed":[9],"to":[10,41,89,106,177],"be":[11,39,67,142],"efficient":[12],"extremely":[14],"large":[15,149],"collections":[16],"of":[17,52,56,59,61,77,151,154],"images.":[18],"For":[19],"each":[20,42,121],"query,":[21,123],"a":[22,29,34,50,74,148,158],"small":[23],"response":[24,46,91,111,137],"set":[25,92,138],"selected":[27],"by":[28,145],"fast":[30],"prefilter,":[31],"after":[32],"more":[35],"accurate":[36],"ranker":[37],"may":[38,141],"applied":[40],"image":[43],"in":[44,86],"the":[45,90,125],"set.":[47,112],"consider":[49],"class":[51,165],"prefilters":[53,95],"comprising":[54],"disjunctions":[55],"conjunctions":[57,153],"(\u201cORs":[58],"ANDs\u201d)":[60],"Boolean":[62,155],"features.":[63],"AND":[64],"filters":[65],"can":[66],"implemented":[68,144],"efficiently":[69,143],"using":[70,157],"skipped":[71],"inverted":[72],"files,":[73],"key":[75],"component":[76],"Web-scale":[78],"text":[79],"engines.":[81],"These":[82],"structures":[83],"permit":[84],"time":[87,105],"proportional":[88],"size.":[93,139],"The":[94],"are":[96],"learned":[97],"from":[98,147],"training":[99],"examples,":[100],"and":[101],"refined":[102],"at":[103],"query":[104],"produce":[107],"approximately":[109],"bounded":[110],"cast":[114],"prefiltering":[115],"as":[116],"optimization":[118],"problem:":[119],"test":[122],"select":[124],"OR-of-AND":[126],"filter":[127,172],"maximizes":[129],"training-set":[130],"recall":[131],"adjustable":[134],"bound":[135],"on":[136,163],"This":[140],"selecting":[146],"pool":[150],"candidate":[152],"features":[156],"linear":[159],"program":[160],"relaxation.":[161],"Tests":[162],"object":[164],"recognition":[166],"show":[167],"that":[168],"this":[169],"relatively":[170],"simple":[171],"nevertheless":[174],"powerful":[175],"enough":[176],"capture":[178],"some":[179],"semantic":[180],"information.":[181]},"counts_by_year":[{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":2},{"year":2017,"cited_by_count":2},{"year":2016,"cited_by_count":1},{"year":2015,"cited_by_count":3},{"year":2014,"cited_by_count":3},{"year":2013,"cited_by_count":2}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}
