{"id":"https://openalex.org/W1970055505","doi":"https://doi.org/10.1109/cvpr.2010.5539928","title":"Data fusion through cross-modality metric learning using similarity-sensitive hashing","display_name":"Data fusion through cross-modality metric learning using similarity-sensitive hashing","publication_year":2010,"publication_date":"2010-06-01","ids":{"openalex":"https://openalex.org/W1970055505","doi":"https://doi.org/10.1109/cvpr.2010.5539928","mag":"1970055505"},"language":"en","primary_location":{"id":"doi:10.1109/cvpr.2010.5539928","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr.2010.5539928","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition","raw_type":"proceedings-article"},"type":"preprint","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/A5013638126","display_name":"Michael M. Bronstein","orcid":"https://orcid.org/0000-0002-1262-7252"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Michael M. Bronstein","raw_affiliation_strings":["Department of Computer Science [Haifa]"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science [Haifa]","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5109277461","display_name":"Alexander M. Bronstein","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Alexander M. Bronstein","raw_affiliation_strings":["Department of Computer Science [Haifa]"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science [Haifa]","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112687797","display_name":"Fabrice Michel","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Fabrice Michel","raw_affiliation_strings":["Organ Modeling through Extraction, Representation and Understanding of Medical Image Content","Centre de vision num\u00e9rique"],"affiliations":[{"raw_affiliation_string":"Organ Modeling through Extraction, Representation and Understanding of Medical Image Content","institution_ids":[]},{"raw_affiliation_string":"Centre de vision num\u00e9rique","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5077223134","display_name":"Nikos Paragios","orcid":"https://orcid.org/0000-0002-9668-4763"},"institutions":[{"id":"https://openalex.org/I4210154111","display_name":"Universit\u00e9 Gustave Eiffel","ror":"https://ror.org/03x42jk29","country_code":"FR","type":"education","lineage":["https://openalex.org/I4210154111"]},{"id":"https://openalex.org/I4210152518","display_name":"Laboratoire d'Informatique Gaspard-Monge","ror":"https://ror.org/04t50yk91","country_code":"FR","type":"facility","lineage":["https://openalex.org/I1294671590","https://openalex.org/I1294671590","https://openalex.org/I142631665","https://openalex.org/I4210145102","https://openalex.org/I4210152518","https://openalex.org/I4210154111","https://openalex.org/I4210159245"]},{"id":"https://openalex.org/I142631665","display_name":"\u00c9cole nationale des ponts et chauss\u00e9es","ror":"https://ror.org/02nwvxz07","country_code":"FR","type":"education","lineage":["https://openalex.org/I142631665","https://openalex.org/I4210145102"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Nikos Paragios","raw_affiliation_strings":["\u00c9cole des Ponts ParisTech","Universit\u00e9 Paris-Est Marne-la-Vall\u00e9e","imagine [Marne-la-Vall\u00e9e]","Organ Modeling through Extraction, Representation and Understanding of Medical Image Content","Math\u00e9matiques Appliqu\u00e9es aux Syst\u00e8mes - EA 4037","Laboratoire d'Informatique Gaspard-Monge"],"affiliations":[{"raw_affiliation_string":"\u00c9cole des Ponts ParisTech","institution_ids":["https://openalex.org/I142631665"]},{"raw_affiliation_string":"Universit\u00e9 Paris-Est Marne-la-Vall\u00e9e","institution_ids":["https://openalex.org/I4210154111"]},{"raw_affiliation_string":"imagine [Marne-la-Vall\u00e9e]","institution_ids":[]},{"raw_affiliation_string":"Organ Modeling through Extraction, Representation and Understanding of Medical Image Content","institution_ids":[]},{"raw_affiliation_string":"Math\u00e9matiques Appliqu\u00e9es aux Syst\u00e8mes - EA 4037","institution_ids":[]},{"raw_affiliation_string":"Laboratoire d'Informatique Gaspard-Monge","institution_ids":["https://openalex.org/I4210152518"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5013638126"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":10.9913,"has_fulltext":false,"cited_by_count":482,"citation_normalized_percentile":{"value":0.98752276,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"3594","last_page":"3601"},"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":0.9991999864578247,"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/T10812","display_name":"Human Pose and Action Recognition","score":0.9968000054359436,"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/hamming-space","display_name":"Hamming space","score":0.7779372930526733},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6745564937591553},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6582545042037964},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5813237428665161},{"id":"https://openalex.org/keywords/boosting","display_name":"Boosting (machine learning)","score":0.544938325881958},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.5182650089263916},{"id":"https://openalex.org/keywords/locality-sensitive-hashing","display_name":"Locality-sensitive hashing","score":0.47672954201698303},{"id":"https://openalex.org/keywords/hamming-distance","display_name":"Hamming distance","score":0.46801695227622986},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.45258980989456177},{"id":"https://openalex.org/keywords/hash-function","display_name":"Hash function","score":0.43922626972198486},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.42921745777130127},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.4217313528060913},{"id":"https://openalex.org/keywords/hamming-code","display_name":"Hamming code","score":0.3755452036857605},{"id":"https://openalex.org/keywords/hash-table","display_name":"Hash table","score":0.17886745929718018},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.12762480974197388},{"id":"https://openalex.org/keywords/decoding-methods","display_name":"Decoding methods","score":0.12119835615158081}],"concepts":[{"id":"https://openalex.org/C2779494224","wikidata":"https://www.wikidata.org/wiki/Q5645799","display_name":"Hamming space","level":5,"score":0.7779372930526733},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6745564937591553},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6582545042037964},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5813237428665161},{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.544938325881958},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.5182650089263916},{"id":"https://openalex.org/C74270461","wikidata":"https://www.wikidata.org/wiki/Q1625299","display_name":"Locality-sensitive hashing","level":4,"score":0.47672954201698303},{"id":"https://openalex.org/C193319292","wikidata":"https://www.wikidata.org/wiki/Q272172","display_name":"Hamming distance","level":2,"score":0.46801695227622986},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.45258980989456177},{"id":"https://openalex.org/C99138194","wikidata":"https://www.wikidata.org/wiki/Q183427","display_name":"Hash function","level":2,"score":0.43922626972198486},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.42921745777130127},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.4217313528060913},{"id":"https://openalex.org/C73150493","wikidata":"https://www.wikidata.org/wiki/Q853922","display_name":"Hamming code","level":4,"score":0.3755452036857605},{"id":"https://openalex.org/C67388219","wikidata":"https://www.wikidata.org/wiki/Q207440","display_name":"Hash table","level":3,"score":0.17886745929718018},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.12762480974197388},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.12119835615158081},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0},{"id":"https://openalex.org/C157125643","wikidata":"https://www.wikidata.org/wiki/Q884707","display_name":"Block code","level":3,"score":0.0},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/cvpr.2010.5539928","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr.2010.5539928","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.211.7102","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.211.7102","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://visl.technion.ac.il/bron/publications/BroBroMicParCVPR10.pdf","raw_type":"text"},{"id":"pmh:oai:HAL:hal-00856061v1","is_oa":false,"landing_page_url":"https://hal.science/hal-00856061","pdf_url":null,"source":{"id":"https://openalex.org/S4406922461","display_name":"SPIRE - Sciences Po Institutional REpository","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":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"23rd IEEE Conference on Computer Vision and Pattern Recognition - CVPR 2010, Jun 2010, San Francisco, United States. pp.3594-3601, ⟨10.1109/CVPR.2010.5539928⟩","raw_type":"Conference papers"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":52,"referenced_works":["https://openalex.org/W158821397","https://openalex.org/W1514177737","https://openalex.org/W1531055819","https://openalex.org/W1556531089","https://openalex.org/W1586283311","https://openalex.org/W1590776313","https://openalex.org/W1597141413","https://openalex.org/W1984527845","https://openalex.org/W1988790447","https://openalex.org/W2001141328","https://openalex.org/W2004537679","https://openalex.org/W2006554089","https://openalex.org/W2012433182","https://openalex.org/W2053186076","https://openalex.org/W2057018318","https://openalex.org/W2097308346","https://openalex.org/W2098979973","https://openalex.org/W2099789128","https://openalex.org/W2100398441","https://openalex.org/W2100657858","https://openalex.org/W2106053110","https://openalex.org/W2110278198","https://openalex.org/W2117154949","https://openalex.org/W2118961645","https://openalex.org/W2122007052","https://openalex.org/W2124404372","https://openalex.org/W2125822693","https://openalex.org/W2130556178","https://openalex.org/W2131846894","https://openalex.org/W2144935315","https://openalex.org/W2147717514","https://openalex.org/W2151103935","https://openalex.org/W2152926413","https://openalex.org/W2154956324","https://openalex.org/W2156857397","https://openalex.org/W2162881463","https://openalex.org/W2166742463","https://openalex.org/W2293597654","https://openalex.org/W3097096317","https://openalex.org/W3099839986","https://openalex.org/W4205380271","https://openalex.org/W4248437541","https://openalex.org/W4252995899","https://openalex.org/W6630938562","https://openalex.org/W6633472159","https://openalex.org/W6635501545","https://openalex.org/W6646261181","https://openalex.org/W6675751002","https://openalex.org/W6676317897","https://openalex.org/W6677328822","https://openalex.org/W6680962578","https://openalex.org/W6697214482"],"related_works":["https://openalex.org/W1993530675","https://openalex.org/W2371167013","https://openalex.org/W2182731056","https://openalex.org/W2613408642","https://openalex.org/W4235868261","https://openalex.org/W1519122282","https://openalex.org/W1503555387","https://openalex.org/W2140899540","https://openalex.org/W2169207476","https://openalex.org/W4380994333"],"abstract_inverted_index":{"Visual":[0],"understanding":[1],"is":[2,98,127],"often":[3,66],"based":[4,82],"on":[5,59,83,129],"measuring":[6],"similarity":[7,54,80],"between":[8,55],"observations.":[9],"Learning":[10],"similarities":[11],"specific":[12],"to":[13,44],"a":[14,19,76,101,124],"certain":[15],"perception":[16],"task":[17],"from":[18,47,88],"set":[20],"of":[21,122,139],"examples":[22],"has":[23],"been":[24],"shown":[25],"advantageous":[26],"in":[27],"various":[28],"computer":[29],"vision":[30],"and":[31,52,65,69,107,110,120,137],"pattern":[32],"recognition":[33],"problems.":[34],"In":[35,71],"many":[36],"important":[37],"applications,":[38],"the":[39,53,85,93],"data":[40,57,87],"that":[41,61],"one":[42],"needs":[43],"compare":[45],"come":[46],"different":[48,64],"representations":[49],"or":[50],"modalities,":[51],"such":[56,123],"operates":[58],"objects":[60],"may":[62],"have":[63],"incommensurable":[67],"structure":[68],"dimensionality.":[70],"this":[72],"paper,":[73],"we":[74],"propose":[75],"framework":[77],"for":[78],"supervised":[79],"learning":[81],"embedding":[84],"input":[86],"two":[89],"arbitrary":[90],"spaces":[91],"into":[92],"Hamming":[94],"space.":[95],"The":[96,118],"mapping":[97],"expressed":[99],"as":[100],"binary":[102],"classification":[103],"problem":[104],"with":[105],"positive":[106],"negative":[108],"examples,":[109],"can":[111],"be":[112],"efficiently":[113],"learned":[114],"using":[115],"boosting":[116],"algorithms.":[117],"utility":[119],"efficiency":[121],"generic":[125],"approach":[126],"demonstrated":[128],"several":[130],"challenging":[131],"applications":[132],"including":[133],"cross-representation":[134],"shape":[135],"retrieval":[136],"alignment":[138],"multi-modal":[140],"medical":[141],"images.":[142],"1.":[143]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":15},{"year":2023,"cited_by_count":29},{"year":2022,"cited_by_count":25},{"year":2021,"cited_by_count":39},{"year":2020,"cited_by_count":43},{"year":2019,"cited_by_count":51},{"year":2018,"cited_by_count":64},{"year":2017,"cited_by_count":53},{"year":2016,"cited_by_count":55},{"year":2015,"cited_by_count":44},{"year":2014,"cited_by_count":25},{"year":2013,"cited_by_count":15},{"year":2012,"cited_by_count":12}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}