{"id":"https://openalex.org/W4282926067","doi":"https://doi.org/10.1109/tnnls.2022.3174970","title":"Graph Convolutional Network Discrete Hashing for Cross-Modal Retrieval","display_name":"Graph Convolutional Network Discrete Hashing for Cross-Modal Retrieval","publication_year":2022,"publication_date":"2022-05-23","ids":{"openalex":"https://openalex.org/W4282926067","doi":"https://doi.org/10.1109/tnnls.2022.3174970","pmid":"https://pubmed.ncbi.nlm.nih.gov/35604998"},"language":"en","primary_location":{"id":"doi:10.1109/tnnls.2022.3174970","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2022.3174970","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Neural Networks and Learning Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5013768600","display_name":"Cong Bai","orcid":"https://orcid.org/0000-0002-6177-3862"},"institutions":[{"id":"https://openalex.org/I55712492","display_name":"Zhejiang University of Technology","ror":"https://ror.org/02djqfd08","country_code":"CN","type":"education","lineage":["https://openalex.org/I55712492"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Cong Bai","raw_affiliation_strings":["Collage of Computer Science, Zhejiang University of Technology and the Key Laboratory of Visual Media Intelligent Processing Technology of Zhejiang Province, Hangzhou, China"],"raw_orcid":"https://orcid.org/0000-0002-6177-3862","affiliations":[{"raw_affiliation_string":"Collage of Computer Science, Zhejiang University of Technology and the Key Laboratory of Visual Media Intelligent Processing Technology of Zhejiang Province, Hangzhou, China","institution_ids":["https://openalex.org/I55712492"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101920642","display_name":"Chao Zeng","orcid":null},"institutions":[{"id":"https://openalex.org/I55712492","display_name":"Zhejiang University of Technology","ror":"https://ror.org/02djqfd08","country_code":"CN","type":"education","lineage":["https://openalex.org/I55712492"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chao Zeng","raw_affiliation_strings":["Collage of Computer Science, Zhejiang University of Technology and the Key Laboratory of Visual Media Intelligent Processing Technology of Zhejiang Province, Hangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Collage of Computer Science, Zhejiang University of Technology and the Key Laboratory of Visual Media Intelligent Processing Technology of Zhejiang Province, Hangzhou, China","institution_ids":["https://openalex.org/I55712492"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101456529","display_name":"Qing Ma","orcid":"https://orcid.org/0000-0002-3902-3635"},"institutions":[{"id":"https://openalex.org/I55712492","display_name":"Zhejiang University of Technology","ror":"https://ror.org/02djqfd08","country_code":"CN","type":"education","lineage":["https://openalex.org/I55712492"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qing Ma","raw_affiliation_strings":["College of Science, Zhejiang University of Technology, Hangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Science, Zhejiang University of Technology, Hangzhou, China","institution_ids":["https://openalex.org/I55712492"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100687480","display_name":"Jinglin Zhang","orcid":"https://orcid.org/0000-0003-1618-8493"},"institutions":[{"id":"https://openalex.org/I154099455","display_name":"Shandong University","ror":"https://ror.org/0207yh398","country_code":"CN","type":"education","lineage":["https://openalex.org/I154099455"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jinglin Zhang","raw_affiliation_strings":["School of Control Science and Engineering, Shandong University, Jinan, China"],"raw_orcid":"https://orcid.org/0000-0003-1618-8493","affiliations":[{"raw_affiliation_string":"School of Control Science and Engineering, Shandong University, Jinan, China","institution_ids":["https://openalex.org/I154099455"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5013768600"],"corresponding_institution_ids":["https://openalex.org/I55712492"],"apc_list":null,"apc_paid":null,"fwci":5.3061,"has_fulltext":false,"cited_by_count":59,"citation_normalized_percentile":{"value":0.96832182,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":"35","issue":"4","first_page":"4756","last_page":"4767"},"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9905999898910522,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9735000133514404,"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":0.7140843272209167},{"id":"https://openalex.org/keywords/hash-function","display_name":"Hash function","score":0.7095538377761841},{"id":"https://openalex.org/keywords/feature-hashing","display_name":"Feature hashing","score":0.5945126414299011},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5709143280982971},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.49718788266181946},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.4956568479537964},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.47797176241874695},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.4700329005718231},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.4128419756889343},{"id":"https://openalex.org/keywords/hash-table","display_name":"Hash table","score":0.36102455854415894},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.346419095993042},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3237959146499634},{"id":"https://openalex.org/keywords/double-hashing","display_name":"Double hashing","score":0.22768205404281616}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7140843272209167},{"id":"https://openalex.org/C99138194","wikidata":"https://www.wikidata.org/wiki/Q183427","display_name":"Hash function","level":2,"score":0.7095538377761841},{"id":"https://openalex.org/C133667856","wikidata":"https://www.wikidata.org/wiki/Q5439682","display_name":"Feature hashing","level":5,"score":0.5945126414299011},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5709143280982971},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.49718788266181946},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.4956568479537964},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.47797176241874695},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.4700329005718231},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.4128419756889343},{"id":"https://openalex.org/C67388219","wikidata":"https://www.wikidata.org/wiki/Q207440","display_name":"Hash table","level":3,"score":0.36102455854415894},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.346419095993042},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3237959146499634},{"id":"https://openalex.org/C138111711","wikidata":"https://www.wikidata.org/wiki/Q478351","display_name":"Double hashing","level":4,"score":0.22768205404281616},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tnnls.2022.3174970","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2022.3174970","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Neural Networks and Learning Systems","raw_type":"journal-article"},{"id":"pmid:35604998","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/35604998","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on neural networks and learning systems","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"No poverty","id":"https://metadata.un.org/sdg/1","score":0.699999988079071}],"awards":[{"id":"https://openalex.org/G3342111343","display_name":null,"funder_award_id":"BE2021093","funder_id":"https://openalex.org/F4320327777","funder_display_name":"Jiangsu Provincial Key Research and Development Program"},{"id":"https://openalex.org/G389909570","display_name":null,"funder_award_id":"62102365","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G491842903","display_name":null,"funder_award_id":"61976192","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7555114670","display_name":null,"funder_award_id":"U20A20196","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8847732984","display_name":null,"funder_award_id":"LR21F020002","funder_id":"https://openalex.org/F4320338464","funder_display_name":"Natural Science Foundation of Zhejiang Province"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320327777","display_name":"Jiangsu Provincial Key Research and Development Program","ror":null},{"id":"https://openalex.org/F4320338464","display_name":"Natural Science Foundation of Zhejiang Province","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":54,"referenced_works":["https://openalex.org/W1861492603","https://openalex.org/W1922199343","https://openalex.org/W1976258951","https://openalex.org/W2007972815","https://openalex.org/W2043478128","https://openalex.org/W2117539524","https://openalex.org/W2155803963","https://openalex.org/W2203543769","https://openalex.org/W2266728343","https://openalex.org/W2538995153","https://openalex.org/W2594227027","https://openalex.org/W2778808770","https://openalex.org/W2788843501","https://openalex.org/W2795832645","https://openalex.org/W2799150641","https://openalex.org/W2801122074","https://openalex.org/W2804165720","https://openalex.org/W2808243243","https://openalex.org/W2894874917","https://openalex.org/W2894879246","https://openalex.org/W2903903916","https://openalex.org/W2911594274","https://openalex.org/W2932399282","https://openalex.org/W2949588459","https://openalex.org/W2953843235","https://openalex.org/W2963187862","https://openalex.org/W2963288100","https://openalex.org/W2964321699","https://openalex.org/W2965009046","https://openalex.org/W2966146145","https://openalex.org/W2992352554","https://openalex.org/W2996002873","https://openalex.org/W2998423439","https://openalex.org/W3001749557","https://openalex.org/W3005609721","https://openalex.org/W3012050760","https://openalex.org/W3014697397","https://openalex.org/W3021853564","https://openalex.org/W3033740891","https://openalex.org/W3033799362","https://openalex.org/W3105543546","https://openalex.org/W3122091215","https://openalex.org/W3127541398","https://openalex.org/W3138366398","https://openalex.org/W3162085601","https://openalex.org/W3183241772","https://openalex.org/W4295312788","https://openalex.org/W6631190155","https://openalex.org/W6688759320","https://openalex.org/W6691431627","https://openalex.org/W6726873649","https://openalex.org/W6738979955","https://openalex.org/W6766978945","https://openalex.org/W6773666150"],"related_works":["https://openalex.org/W4381744218","https://openalex.org/W2767764284","https://openalex.org/W2144265691","https://openalex.org/W2059244188","https://openalex.org/W1981124010","https://openalex.org/W3192025065","https://openalex.org/W3087964089","https://openalex.org/W4205587245","https://openalex.org/W4211126162","https://openalex.org/W3158263601"],"abstract_inverted_index":{"With":[0],"the":[1,15,29,43,63,76,80,113,163,181,216,242],"rapid":[2],"development":[3],"of":[4,17,20,31,42,65,75,169,187],"deep":[5],"neural":[6],"networks,":[7],"cross-modal":[8,245],"hashing":[9,239,246],"has":[10],"made":[11],"great":[12],"progress.":[13],"However,":[14,46],"information":[16,64,164],"different":[18,167],"types":[19,168],"data":[21],"is":[22,25,34,54],"asymmetrical,":[23],"that":[24,62,135,231],"to":[26,102,107,161,199,214],"say,":[27],"if":[28],"resolution":[30],"an":[32,209],"image":[33,66],"high":[35],"enough,":[36,57],"it":[37,53],"can":[38,173,195],"reproduce":[39],"almost":[40],"100%":[41],"real-world":[44],"scenes.":[45],"text":[47],"usually":[48],"carries":[49],"personal":[50],"emotion":[51],"and":[52,84,96,117],"not":[55,98],"objective":[56],"so":[58],"we":[59,144,194,207],"generally":[60],"think":[61],"will":[67],"be":[68],"much":[69],"richer":[70],"than":[71],"text.":[72],"Although":[73],"most":[74],"existing":[77],"methods":[78,127],"unify":[79,112],"semantic":[81,114],"feature":[82,115,201],"extraction":[83,116],"hash":[85,118,129],"function":[86,119],"learning":[87,120],"modules":[88,121],"for":[89,122],"end-to-end":[90,123],"learning,":[91],"they":[92,111],"ignore":[93],"this":[94],"issue":[95],"do":[97],"use":[99,208],"information-rich":[100],"modalities":[101],"support":[103],"information-poor":[104],"modalities,":[105],"leading":[106],"suboptimal":[108],"results,":[109],"although":[110],"learning.":[124],"Furthermore,":[125],"previous":[126],"learn":[128,215],"functions":[130],"in":[131],"a":[132,146,159,185],"relaxed":[133],"way":[134],"causes":[136],"nontrivial":[137],"quantization":[138],"losses.":[139],"To":[140],"address":[141],"these":[142,192],"issues,":[143],"propose":[145],"new":[147],"method":[148,157,234],"called":[149],"graph":[150,235],"convolutional":[151,236],"network":[152],"(GCN)":[153],"discrete":[154,211,217,238],"hashing.":[155],"This":[156],"uses":[158],"GCN":[160,172],"bridge":[162],"gap":[165],"between":[166],"data.":[170],"The":[171],"represent":[174],"each":[175],"label":[176],"as":[177,184],"word":[178],"embedding,":[179],"with":[180],"embedding":[182],"regarded":[183],"set":[186],"interdependent":[188],"object":[189],"classifiers.":[190],"From":[191],"classifiers,":[193],"obtain":[196],"predicted":[197],"labels":[198],"enhance":[200],"representations":[202],"across":[203],"modalities.":[204],"In":[205],"addition,":[206],"efficient":[210],"optimization":[212],"strategy":[213],"binary":[218],"codes":[219],"without":[220],"relaxation.":[221],"Extensive":[222],"experiments":[223],"conducted":[224],"on":[225],"three":[226],"commonly":[227],"used":[228],"datasets":[229],"demonstrate":[230],"our":[232],"proposed":[233],"network-based":[237],"(GCDH)":[240],"outperforms":[241],"current":[243],"state-of-the-art":[244],"methods.":[247]},"counts_by_year":[{"year":2026,"cited_by_count":7},{"year":2025,"cited_by_count":27},{"year":2024,"cited_by_count":12},{"year":2023,"cited_by_count":13}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}