{"id":"https://openalex.org/W3025709990","doi":"https://doi.org/10.1109/wacv45572.2020.9093487","title":"Image Hashing via Linear Discriminant Learning","display_name":"Image Hashing via Linear Discriminant Learning","publication_year":2020,"publication_date":"2020-03-01","ids":{"openalex":"https://openalex.org/W3025709990","doi":"https://doi.org/10.1109/wacv45572.2020.9093487","mag":"3025709990"},"language":"en","primary_location":{"id":"doi:10.1109/wacv45572.2020.9093487","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wacv45572.2020.9093487","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE Winter Conference on Applications of Computer Vision (WACV)","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/A5054872468","display_name":"Weixiang Hong","orcid":"https://orcid.org/0000-0002-3794-3972"},"institutions":[{"id":"https://openalex.org/I165932596","display_name":"National University of Singapore","ror":"https://ror.org/01tgyzw49","country_code":"SG","type":"education","lineage":["https://openalex.org/I165932596"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Weixiang Hong","raw_affiliation_strings":["National University of Singapore"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National University of Singapore","institution_ids":["https://openalex.org/I165932596"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101562708","display_name":"Yu-Ting Chang","orcid":"https://orcid.org/0000-0001-7365-8709"},"institutions":[{"id":"https://openalex.org/I156087764","display_name":"University of California, Merced","ror":"https://ror.org/00d9ah105","country_code":"US","type":"education","lineage":["https://openalex.org/I156087764"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yu-Ting Chang","raw_affiliation_strings":["UC Merced"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"UC Merced","institution_ids":["https://openalex.org/I156087764"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5019857598","display_name":"Haifang Qin","orcid":"https://orcid.org/0009-0004-4649-4090"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haifang Qin","raw_affiliation_strings":["Peking University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Peking University","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5064935846","display_name":"Wei-Chih Hung","orcid":null},"institutions":[{"id":"https://openalex.org/I156087764","display_name":"University of California, Merced","ror":"https://ror.org/00d9ah105","country_code":"US","type":"education","lineage":["https://openalex.org/I156087764"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Wei-Chih Hung","raw_affiliation_strings":["UC Merced"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"UC Merced","institution_ids":["https://openalex.org/I156087764"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112904753","display_name":"Yi\u2013Hsuan Tsai","orcid":"https://orcid.org/0000-0003-2107-4300"},"institutions":[{"id":"https://openalex.org/I4210107353","display_name":"NEC (United States)","ror":"https://ror.org/01v791m31","country_code":"US","type":"company","lineage":["https://openalex.org/I118347220","https://openalex.org/I4210107353"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yi-Hsuan Tsai","raw_affiliation_strings":["NEC Labs America"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"NEC Labs America","institution_ids":["https://openalex.org/I4210107353"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100418319","display_name":"Ming\u2013Hsuan Yang","orcid":"https://orcid.org/0000-0003-4848-2304"},"institutions":[{"id":"https://openalex.org/I1291425158","display_name":"Google (United States)","ror":"https://ror.org/00njsd438","country_code":"US","type":"company","lineage":["https://openalex.org/I1291425158","https://openalex.org/I4210128969"]},{"id":"https://openalex.org/I156087764","display_name":"University of California, Merced","ror":"https://ror.org/00d9ah105","country_code":"US","type":"education","lineage":["https://openalex.org/I156087764"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ming-Hsuan Yang","raw_affiliation_strings":["UC Merced/Google"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"UC Merced/Google","institution_ids":["https://openalex.org/I1291425158","https://openalex.org/I156087764"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":6,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.2726,"has_fulltext":false,"cited_by_count":14,"citation_normalized_percentile":{"value":0.8236141,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":"34","issue":null,"first_page":"2520","last_page":"2528"},"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9966999888420105,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9919000267982483,"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/discriminative-model","display_name":"Discriminative model","score":0.800460696220398},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7614655494689941},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7256497740745544},{"id":"https://openalex.org/keywords/hash-function","display_name":"Hash function","score":0.7209678292274475},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.66731858253479},{"id":"https://openalex.org/keywords/image-retrieval","display_name":"Image retrieval","score":0.6324378252029419},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5952625870704651},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5619635581970215},{"id":"https://openalex.org/keywords/binary-code","display_name":"Binary code","score":0.5445795655250549},{"id":"https://openalex.org/keywords/feature-hashing","display_name":"Feature hashing","score":0.5129887461662292},{"id":"https://openalex.org/keywords/linear-discriminant-analysis","display_name":"Linear discriminant analysis","score":0.5065382719039917},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.43333011865615845},{"id":"https://openalex.org/keywords/binary-number","display_name":"Binary number","score":0.3894025385379791},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.36795780062675476},{"id":"https://openalex.org/keywords/hash-table","display_name":"Hash table","score":0.24402189254760742},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.130232036113739}],"concepts":[{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.800460696220398},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7614655494689941},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7256497740745544},{"id":"https://openalex.org/C99138194","wikidata":"https://www.wikidata.org/wiki/Q183427","display_name":"Hash function","level":2,"score":0.7209678292274475},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.66731858253479},{"id":"https://openalex.org/C1667742","wikidata":"https://www.wikidata.org/wiki/Q10927554","display_name":"Image retrieval","level":3,"score":0.6324378252029419},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5952625870704651},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5619635581970215},{"id":"https://openalex.org/C63435697","wikidata":"https://www.wikidata.org/wiki/Q864135","display_name":"Binary code","level":3,"score":0.5445795655250549},{"id":"https://openalex.org/C133667856","wikidata":"https://www.wikidata.org/wiki/Q5439682","display_name":"Feature hashing","level":5,"score":0.5129887461662292},{"id":"https://openalex.org/C69738355","wikidata":"https://www.wikidata.org/wiki/Q1228929","display_name":"Linear discriminant analysis","level":2,"score":0.5065382719039917},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.43333011865615845},{"id":"https://openalex.org/C48372109","wikidata":"https://www.wikidata.org/wiki/Q3913","display_name":"Binary number","level":2,"score":0.3894025385379791},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.36795780062675476},{"id":"https://openalex.org/C67388219","wikidata":"https://www.wikidata.org/wiki/Q207440","display_name":"Hash table","level":3,"score":0.24402189254760742},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.130232036113739},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0},{"id":"https://openalex.org/C94375191","wikidata":"https://www.wikidata.org/wiki/Q11205","display_name":"Arithmetic","level":1,"score":0.0},{"id":"https://openalex.org/C138111711","wikidata":"https://www.wikidata.org/wiki/Q478351","display_name":"Double hashing","level":4,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/wacv45572.2020.9093487","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wacv45572.2020.9093487","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE Winter Conference on Applications of Computer Vision (WACV)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","score":0.7300000190734863,"display_name":"Reduced inequalities"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":62,"referenced_works":["https://openalex.org/W1502916507","https://openalex.org/W1883985887","https://openalex.org/W1902934009","https://openalex.org/W1910300841","https://openalex.org/W1939575207","https://openalex.org/W1943357268","https://openalex.org/W1956333070","https://openalex.org/W1992371516","https://openalex.org/W2001619934","https://openalex.org/W2007972815","https://openalex.org/W2084363474","https://openalex.org/W2117539524","https://openalex.org/W2130540277","https://openalex.org/W2134514757","https://openalex.org/W2142881874","https://openalex.org/W2155541015","https://openalex.org/W2163605009","https://openalex.org/W2171790913","https://openalex.org/W2187089797","https://openalex.org/W2194775991","https://openalex.org/W2293597654","https://openalex.org/W2293824885","https://openalex.org/W2300242332","https://openalex.org/W2411707397","https://openalex.org/W2464915613","https://openalex.org/W2508837377","https://openalex.org/W2520774990","https://openalex.org/W2526140607","https://openalex.org/W2531549126","https://openalex.org/W2562322388","https://openalex.org/W2565993688","https://openalex.org/W2586937979","https://openalex.org/W2621176975","https://openalex.org/W2737652487","https://openalex.org/W2897765688","https://openalex.org/W2963114950","https://openalex.org/W2963276379","https://openalex.org/W2963398644","https://openalex.org/W2963540428","https://openalex.org/W2963892472","https://openalex.org/W2964280870","https://openalex.org/W3118608800","https://openalex.org/W4293380554","https://openalex.org/W4294375521","https://openalex.org/W6629956336","https://openalex.org/W6639703010","https://openalex.org/W6648560114","https://openalex.org/W6679406034","https://openalex.org/W6681077227","https://openalex.org/W6682778277","https://openalex.org/W6684191040","https://openalex.org/W6688152296","https://openalex.org/W6692658850","https://openalex.org/W6697214482","https://openalex.org/W6698200048","https://openalex.org/W6726946684","https://openalex.org/W6728449338","https://openalex.org/W6731107727","https://openalex.org/W6733147417","https://openalex.org/W6738979955","https://openalex.org/W6755620697","https://openalex.org/W6787972765"],"related_works":["https://openalex.org/W4381744218","https://openalex.org/W2767764284","https://openalex.org/W2059244188","https://openalex.org/W2035647105","https://openalex.org/W1981124010","https://openalex.org/W3192025065","https://openalex.org/W3087964089","https://openalex.org/W4205587245","https://openalex.org/W2088296667","https://openalex.org/W2963758661"],"abstract_inverted_index":{"Hashing":[0],"has":[1,30],"attracted":[2],"attention":[3],"in":[4,24,44,74,80],"recent":[5,22],"years":[6],"due":[7],"to":[8,96],"the":[9,18,83],"rapid":[10],"growth":[11],"of":[12,49,86],"image":[13,35,112],"and":[14,63,76,104,122],"video":[15],"data":[16,45],"on":[17,118],"web.":[19],"Benefiting":[20],"from":[21],"advances":[23],"deep":[25,27,94,131],"learning,":[26],"supervised":[28,132],"hashing":[29,68,133],"achieved":[31],"promising":[32],"results":[33],"for":[34,111],"retrieval.":[36,81,113],"However,":[37],"existing":[38,129],"methods":[39],"are":[40,101],"either":[41],"less":[42],"efficient":[43,73],"usage":[46],"or":[47],"incapable":[48],"learning":[50],"linearly":[51],"discriminative":[52,61,67],"binary":[53,98],"codes.":[54],"In":[55],"this":[56],"paper,":[57],"we":[58,90],"revisit":[59],"linear":[60,66],"analysis":[62],"propose":[64],"a":[65,87,92],"(LDH)":[69],"objective":[70],"that":[71,100],"is":[72],"training":[75],"achieves":[77],"better":[78,109],"accuracy":[79],"With":[82],"joint":[84],"supervision":[85],"classification":[88],"loss,":[89],"design":[91],"robust":[93],"network":[95],"obtain":[97],"codes":[99],"inter-class":[102],"separable":[103],"intra-class":[105],"compact,":[106],"which":[107],"provides":[108],"representations":[110],"We":[114],"conduct":[115],"extensive":[116],"experiments":[117],"three":[119],"benchmark":[120],"datasets,":[121],"our":[123],"LDH":[124],"algorithm":[125],"performs":[126],"favorably":[127],"against":[128],"state-of-the-art":[130],"methods.":[134]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":6},{"year":2021,"cited_by_count":4}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}