{"id":"https://openalex.org/W2100839471","doi":"https://doi.org/10.1145/1991996.1992012","title":"Lost in binarization","display_name":"Lost in binarization","publication_year":2011,"publication_date":"2011-04-18","ids":{"openalex":"https://openalex.org/W2100839471","doi":"https://doi.org/10.1145/1991996.1992012","mag":"2100839471"},"language":"en","primary_location":{"id":"doi:10.1145/1991996.1992012","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1991996.1992012","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 1st ACM International Conference on Multimedia Retrieval","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/A5047962986","display_name":"Yu\u2013Gang Jiang","orcid":"https://orcid.org/0000-0002-1907-8567"},"institutions":[{"id":"https://openalex.org/I78577930","display_name":"Columbia University","ror":"https://ror.org/00hj8s172","country_code":"US","type":"education","lineage":["https://openalex.org/I78577930"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Yu-Gang Jiang","raw_affiliation_strings":["Columbia University, New York, NY","Columbia University, New York, NY;"],"affiliations":[{"raw_affiliation_string":"Columbia University, New York, NY","institution_ids":["https://openalex.org/I78577930"]},{"raw_affiliation_string":"Columbia University, New York, NY;","institution_ids":["https://openalex.org/I78577930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100384767","display_name":"Jun Wang","orcid":"https://orcid.org/0000-0002-5890-0365"},"institutions":[{"id":"https://openalex.org/I4210114115","display_name":"IBM Research - Thomas J. Watson Research Center","ror":"https://ror.org/0265w5591","country_code":"US","type":"facility","lineage":["https://openalex.org/I1341412227","https://openalex.org/I4210114115"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jun Wang","raw_affiliation_strings":["IBM T. J. Watson Research Center, Yorktown Heights, NY","IBM -- T. J. Watson Research Center, Yorktown Heights, NY"],"affiliations":[{"raw_affiliation_string":"IBM T. J. Watson Research Center, Yorktown Heights, NY","institution_ids":["https://openalex.org/I4210114115"]},{"raw_affiliation_string":"IBM -- T. J. Watson Research Center, Yorktown Heights, NY","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5037340457","display_name":"Shih\u2010Fu Chang","orcid":"https://orcid.org/0000-0003-1444-1205"},"institutions":[{"id":"https://openalex.org/I78577930","display_name":"Columbia University","ror":"https://ror.org/00hj8s172","country_code":"US","type":"education","lineage":["https://openalex.org/I78577930"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Shih-Fu Chang","raw_affiliation_strings":["Columbia University, New York, NY","Columbia University, New York, NY;"],"affiliations":[{"raw_affiliation_string":"Columbia University, New York, NY","institution_ids":["https://openalex.org/I78577930"]},{"raw_affiliation_string":"Columbia University, New York, NY;","institution_ids":["https://openalex.org/I78577930"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5047962986"],"corresponding_institution_ids":["https://openalex.org/I78577930"],"apc_list":null,"apc_paid":null,"fwci":4.6363,"has_fulltext":false,"cited_by_count":45,"citation_normalized_percentile":{"value":0.9581411,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"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":0.9998999834060669,"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":0.9998999834060669,"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":0.9987999796867371,"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/T10689","display_name":"Remote-Sensing Image Classification","score":0.9873999953269958,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/hamming-space","display_name":"Hamming space","score":0.7995025515556335},{"id":"https://openalex.org/keywords/hamming-distance","display_name":"Hamming distance","score":0.7975013852119446},{"id":"https://openalex.org/keywords/hamming-code","display_name":"Hamming code","score":0.6394109129905701},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5643948316574097},{"id":"https://openalex.org/keywords/ranking","display_name":"Ranking (information retrieval)","score":0.5555501580238342},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5101030468940735},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4965510964393616},{"id":"https://openalex.org/keywords/hamming-weight","display_name":"Hamming weight","score":0.4604440927505493},{"id":"https://openalex.org/keywords/hamming-graph","display_name":"Hamming graph","score":0.4537643492221832},{"id":"https://openalex.org/keywords/hamming","display_name":"Hamming(7,4)","score":0.4485699236392975},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.4189501702785492},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.30372413992881775},{"id":"https://openalex.org/keywords/block-code","display_name":"Block code","score":0.12550660967826843}],"concepts":[{"id":"https://openalex.org/C2779494224","wikidata":"https://www.wikidata.org/wiki/Q5645799","display_name":"Hamming space","level":5,"score":0.7995025515556335},{"id":"https://openalex.org/C193319292","wikidata":"https://www.wikidata.org/wiki/Q272172","display_name":"Hamming distance","level":2,"score":0.7975013852119446},{"id":"https://openalex.org/C73150493","wikidata":"https://www.wikidata.org/wiki/Q853922","display_name":"Hamming code","level":4,"score":0.6394109129905701},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5643948316574097},{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.5555501580238342},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5101030468940735},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4965510964393616},{"id":"https://openalex.org/C63361517","wikidata":"https://www.wikidata.org/wiki/Q5645805","display_name":"Hamming weight","level":5,"score":0.4604440927505493},{"id":"https://openalex.org/C29696283","wikidata":"https://www.wikidata.org/wiki/Q369440","display_name":"Hamming graph","level":5,"score":0.4537643492221832},{"id":"https://openalex.org/C112932734","wikidata":"https://www.wikidata.org/wiki/Q2322550","display_name":"Hamming(7,4)","level":5,"score":0.4485699236392975},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4189501702785492},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.30372413992881775},{"id":"https://openalex.org/C157125643","wikidata":"https://www.wikidata.org/wiki/Q884707","display_name":"Block code","level":3,"score":0.12550660967826843},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/1991996.1992012","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1991996.1992012","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 1st ACM International Conference on Multimedia Retrieval","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G5934489420","display_name":null,"funder_award_id":"CNS-07-51078","funder_id":"https://openalex.org/F4320337388","funder_display_name":"Division of Computer and Network Systems"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320337388","display_name":"Division of Computer and Network Systems","ror":"https://ror.org/02rdzmk74"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":42,"referenced_works":["https://openalex.org/W73389528","https://openalex.org/W1566135517","https://openalex.org/W1627400044","https://openalex.org/W1986482242","https://openalex.org/W2001619934","https://openalex.org/W2007972815","https://openalex.org/W2014987111","https://openalex.org/W2044195942","https://openalex.org/W2045806863","https://openalex.org/W2071731678","https://openalex.org/W2088866137","https://openalex.org/W2091503252","https://openalex.org/W2100495367","https://openalex.org/W2111993661","https://openalex.org/W2116064496","https://openalex.org/W2117154949","https://openalex.org/W2121713321","https://openalex.org/W2128017662","https://openalex.org/W2130660124","https://openalex.org/W2131846894","https://openalex.org/W2138662031","https://openalex.org/W2144935315","https://openalex.org/W2145607950","https://openalex.org/W2147682847","https://openalex.org/W2147717514","https://openalex.org/W2151103935","https://openalex.org/W2152926413","https://openalex.org/W2154956324","https://openalex.org/W2157465536","https://openalex.org/W2164338181","https://openalex.org/W2165428671","https://openalex.org/W2165558283","https://openalex.org/W2171448996","https://openalex.org/W2171790913","https://openalex.org/W2293597654","https://openalex.org/W2397770138","https://openalex.org/W2543932557","https://openalex.org/W2913932916","https://openalex.org/W6680962578","https://openalex.org/W6684181414","https://openalex.org/W6697214482","https://openalex.org/W6758860047"],"related_works":["https://openalex.org/W2008960744","https://openalex.org/W2105471374","https://openalex.org/W2613408642","https://openalex.org/W2364868136","https://openalex.org/W2982774419","https://openalex.org/W1966523540","https://openalex.org/W1519122282","https://openalex.org/W2158117886","https://openalex.org/W2182731056","https://openalex.org/W1981727981"],"abstract_inverted_index":{"With":[0,179],"the":[1,6,57,107,124,156,170,176,180,184,203],"proliferation":[2],"of":[3,10,40,49,72,123,131],"images":[4,13,73,108,186],"on":[5,37,211],"Web,":[7],"fast":[8],"search":[9,30,88],"visually":[11],"similar":[12],"has":[14],"attracted":[15],"significant":[16],"attention.":[17],"State-of-the-art":[18],"techniques":[19],"often":[20,68],"embed":[21],"high-dimensional":[22],"visual":[23],"features":[24,52],"into":[25],"low-dimensional":[26],"Hamming":[27,38,58,76,111,192,206],"space,":[28],"where":[29,89],"can":[31,187],"be":[32,188],"performed":[33],"in":[34,82,155],"real-time":[35],"based":[36],"distance":[39,150,193,207],"compact":[41],"binary":[42,125,197],"codes.":[43],"Unlike":[44],"traditional":[45],"metrics":[46],"(e.g.,":[47],"Euclidean)":[48],"raw":[50,158],"image":[51,87,159,214],"that":[53,102,147],"produce":[54],"continuous":[55],"distance,":[56],"distances":[59,77],"are":[60,67,164],"discrete":[61],"integer":[62,205],"values.":[63],"In":[64,94],"practice,":[65],"there":[66],"a":[69,79,83,99,128,143,173,195,212],"large":[70],"number":[71],"sharing":[74],"equal":[75,110],"to":[78],"query,":[80],"resulting":[81],"critical":[84],"issue":[85],"for":[86,106,127],"ranking":[90,105,222],"is":[91,140],"very":[92],"important.":[93],"this":[95,115],"paper,":[96],"we":[97],"propose":[98],"novel":[100],"approach":[101],"facilitates":[103],"query-adaptive":[104,221],"with":[109],"distance.":[112],"We":[113],"achieve":[114],"goal":[116],"by":[117,168,190],"firstly":[118],"offline":[119],"learning":[120,138],"bit":[121,182],"weights":[122,163],"codes":[126],"diverse":[129],"set":[130],"predefined":[132],"semantic":[133],"concept":[134,177],"classes.":[135],"The":[136],"weight":[137],"process":[139],"formulated":[141],"as":[142],"quadratic":[144],"programming":[145],"problem":[146],"minimizes":[148],"intra-class":[149],"while":[151],"preserving":[152],"interclass":[153],"relationship":[154],"original":[157,204],"feature":[160],"space.":[161],"Query-adaptive":[162],"then":[165],"rapidly":[166],"computed":[167],"evaluating":[169],"proximity":[171],"between":[172],"query":[174],"and":[175],"categories.":[178],"adaptive":[181],"weights,":[183],"returned":[185],"ordered":[189],"weighted":[191],"at":[194,202],"finer-grained":[196],"code":[198],"level":[199],"rather":[200],"than":[201],"level.":[208],"Experimental":[209],"results":[210],"Flickr":[213],"dataset":[215],"show":[216],"clear":[217],"improvements":[218],"from":[219],"our":[220],"approach.":[223]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":6},{"year":2016,"cited_by_count":7},{"year":2015,"cited_by_count":7},{"year":2014,"cited_by_count":7},{"year":2013,"cited_by_count":3},{"year":2012,"cited_by_count":8}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}