{"id":"https://openalex.org/W2808273153","doi":"https://doi.org/10.1109/icaci.2018.8377590","title":"Distance metric learning for semantic segmentation based graph hashing","display_name":"Distance metric learning for semantic segmentation based graph hashing","publication_year":2018,"publication_date":"2018-03-01","ids":{"openalex":"https://openalex.org/W2808273153","doi":"https://doi.org/10.1109/icaci.2018.8377590","mag":"2808273153"},"language":"en","primary_location":{"id":"doi:10.1109/icaci.2018.8377590","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icaci.2018.8377590","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 Tenth International Conference on Advanced Computational Intelligence (ICACI)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5056953478","display_name":"Haifeng Hu","orcid":"https://orcid.org/0000-0002-4884-323X"},"institutions":[{"id":"https://openalex.org/I41198531","display_name":"Nanjing University of Posts and Telecommunications","ror":"https://ror.org/043bpky34","country_code":"CN","type":"education","lineage":["https://openalex.org/I41198531"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haifeng Hu","raw_affiliation_strings":["Department of Telecommunication and Information Engineering, NJUPT, Nanjing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Telecommunication and Information Engineering, NJUPT, Nanjing, China","institution_ids":["https://openalex.org/I41198531"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101743130","display_name":"Xiangfeng Xu","orcid":"https://orcid.org/0000-0002-4597-9481"},"institutions":[{"id":"https://openalex.org/I41198531","display_name":"Nanjing University of Posts and Telecommunications","ror":"https://ror.org/043bpky34","country_code":"CN","type":"education","lineage":["https://openalex.org/I41198531"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiangfeng Xu","raw_affiliation_strings":["College of Telecommunication and Information Engineering, NJUPT, Nanjing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Telecommunication and Information Engineering, NJUPT, Nanjing, China","institution_ids":["https://openalex.org/I41198531"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102847901","display_name":"Jiansheng Wu","orcid":"https://orcid.org/0000-0002-7941-9722"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jiansheng Wu","raw_affiliation_strings":["College of Geographic and Biologic Information, NJUPT, Nanjing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Geographic and Biologic Information, NJUPT, Nanjing, China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"abs 1502 717","issue":null,"first_page":"109","last_page":"115"},"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":0.9933000206947327,"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":0.9828000068664551,"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":0.710660457611084},{"id":"https://openalex.org/keywords/dynamic-perfect-hashing","display_name":"Dynamic perfect hashing","score":0.642471194267273},{"id":"https://openalex.org/keywords/hash-function","display_name":"Hash function","score":0.611504077911377},{"id":"https://openalex.org/keywords/semantic-similarity","display_name":"Semantic similarity","score":0.5632925629615784},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5459082126617432},{"id":"https://openalex.org/keywords/universal-hashing","display_name":"Universal hashing","score":0.47491252422332764},{"id":"https://openalex.org/keywords/locality-sensitive-hashing","display_name":"Locality-sensitive hashing","score":0.469659686088562},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4650723934173584},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.4383327066898346},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.4356302320957184},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.3720991611480713},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.321130633354187},{"id":"https://openalex.org/keywords/hash-table","display_name":"Hash table","score":0.29975295066833496},{"id":"https://openalex.org/keywords/double-hashing","display_name":"Double hashing","score":0.21033069491386414}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.710660457611084},{"id":"https://openalex.org/C122907437","wikidata":"https://www.wikidata.org/wiki/Q5318999","display_name":"Dynamic perfect hashing","level":5,"score":0.642471194267273},{"id":"https://openalex.org/C99138194","wikidata":"https://www.wikidata.org/wiki/Q183427","display_name":"Hash function","level":2,"score":0.611504077911377},{"id":"https://openalex.org/C130318100","wikidata":"https://www.wikidata.org/wiki/Q2268914","display_name":"Semantic similarity","level":2,"score":0.5632925629615784},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5459082126617432},{"id":"https://openalex.org/C116058348","wikidata":"https://www.wikidata.org/wiki/Q846912","display_name":"Universal hashing","level":5,"score":0.47491252422332764},{"id":"https://openalex.org/C74270461","wikidata":"https://www.wikidata.org/wiki/Q1625299","display_name":"Locality-sensitive hashing","level":4,"score":0.469659686088562},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4650723934173584},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.4383327066898346},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.4356302320957184},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3720991611480713},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.321130633354187},{"id":"https://openalex.org/C67388219","wikidata":"https://www.wikidata.org/wiki/Q207440","display_name":"Hash table","level":3,"score":0.29975295066833496},{"id":"https://openalex.org/C138111711","wikidata":"https://www.wikidata.org/wiki/Q478351","display_name":"Double hashing","level":4,"score":0.21033069491386414},{"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/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icaci.2018.8377590","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icaci.2018.8377590","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 Tenth International Conference on Advanced Computational Intelligence (ICACI)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":31,"referenced_works":["https://openalex.org/W146125889","https://openalex.org/W1808966389","https://openalex.org/W1910300841","https://openalex.org/W1974647172","https://openalex.org/W1981036287","https://openalex.org/W1992371516","https://openalex.org/W1996936615","https://openalex.org/W1997107867","https://openalex.org/W2031489346","https://openalex.org/W2056935845","https://openalex.org/W2089632823","https://openalex.org/W2100588357","https://openalex.org/W2110226872","https://openalex.org/W2127723919","https://openalex.org/W2129026672","https://openalex.org/W2135596962","https://openalex.org/W2142126424","https://openalex.org/W2144467493","https://openalex.org/W2182822465","https://openalex.org/W2240204456","https://openalex.org/W2251864938","https://openalex.org/W2402125293","https://openalex.org/W2403689645","https://openalex.org/W2510911086","https://openalex.org/W6638519727","https://openalex.org/W6648560114","https://openalex.org/W6686272741","https://openalex.org/W6691474080","https://openalex.org/W6712733126","https://openalex.org/W6713632385","https://openalex.org/W6725774388"],"related_works":["https://openalex.org/W2100189723","https://openalex.org/W2184777945","https://openalex.org/W1551533237","https://openalex.org/W4251536634","https://openalex.org/W1870428314","https://openalex.org/W2088296667","https://openalex.org/W2185281229","https://openalex.org/W1998749283","https://openalex.org/W2962718115","https://openalex.org/W2059096784"],"abstract_inverted_index":{"Similarity":[0],"search":[1,35],"in":[2,10,18],"large-scale":[3],"dataset":[4],"has":[5],"been":[6],"the":[7,11,67,72,76,88,102,122,126,130,137],"key":[8],"technology":[9],"fields":[12],"of":[13,132],"computer":[14],"vision":[15],"and":[16,28,78,96,125],"multimedia":[17],"recent":[19],"years.":[20],"In":[21,42],"order":[22],"to":[23,70,107],"support":[24],"fine-grained":[25],"image":[26,29],"analysis":[27,128],"retrieval,":[30],"semantic":[31,50,73],"segmentation":[32,51],"based":[33,52],"multi-instances":[34],"is":[36,57,85],"becoming":[37],"an":[38,61,81],"urgent":[39],"research":[40],"issue.":[41],"this":[43],"paper,":[44],"a":[45],"distance":[46,63],"metric":[47,64],"learning":[48],"for":[49,87,114],"graph":[53,104],"hashing":[54,105,139],"(MLSS)":[55],"approach":[56,135],"proposed,":[58],"which":[59],"learns":[60],"optimal":[62],"by":[65,91],"minimizing":[66],"objective":[68,89],"function":[69,90],"preserve":[71],"similarity":[74,115],"between":[75],"labels":[77],"instances.":[79],"Then,":[80],"alternating":[82],"optimization":[83],"strategy":[84],"designed":[86],"using":[92],"gradient":[93],"descent":[94],"method":[95,106],"Rayleigh-Ritz":[97],"theorem.":[98],"Finally,":[99],"we":[100],"use":[101],"anchor":[103],"hash":[108],"all":[109],"instances":[110],"into":[111],"binary":[112],"codes":[113],"search.":[116],"Multiple":[117],"experiments":[118],"are":[119],"conducted":[120],"on":[121],"public":[123],"datasets":[124],"comparative":[127],"validate":[129],"advantage":[131],"our":[133],"proposed":[134],"over":[136],"existing":[138],"methods.":[140]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}