{"id":"https://openalex.org/W4225665842","doi":"https://doi.org/10.1109/tip.2022.3163571","title":"Local Semantic Correlation Modeling Over Graph Neural Networks for Deep Feature Embedding and Image Retrieval","display_name":"Local Semantic Correlation Modeling Over Graph Neural Networks for Deep Feature Embedding and Image Retrieval","publication_year":2022,"publication_date":"2022-01-01","ids":{"openalex":"https://openalex.org/W4225665842","doi":"https://doi.org/10.1109/tip.2022.3163571","pmid":"https://pubmed.ncbi.nlm.nih.gov/35380963"},"language":"en","primary_location":{"id":"doi:10.1109/tip.2022.3163571","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2022.3163571","pdf_url":null,"source":{"id":"https://openalex.org/S4210173141","display_name":"IEEE Transactions on Image Processing","issn_l":"1057-7149","issn":["1057-7149","1941-0042"],"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 Image Processing","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":null,"display_name":"Shichao Kan","orcid":"https://orcid.org/0000-0003-0097-6196"},"institutions":[{"id":"https://openalex.org/I139660479","display_name":"Central South University","ror":"https://ror.org/00f1zfq44","country_code":"CN","type":"education","lineage":["https://openalex.org/I139660479"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shichao Kan","raw_affiliation_strings":["School of Computer Science and Engineering, Central South University, Hunan, Changsha, China"],"raw_orcid":"https://orcid.org/0000-0003-0097-6196","affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Central South University, Hunan, Changsha, China","institution_ids":["https://openalex.org/I139660479"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Yigang Cen","orcid":"https://orcid.org/0000-0001-6255-9422"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yigang Cen","raw_affiliation_strings":["Institute of Information Science, Beijing Jiaotong University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0001-6255-9422","affiliations":[{"raw_affiliation_string":"Institute of Information Science, Beijing Jiaotong University, Beijing, China","institution_ids":["https://openalex.org/I21193070"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Yang Li","orcid":"https://orcid.org/0000-0002-8372-1481"},"institutions":[{"id":"https://openalex.org/I14245010","display_name":"University of Kragujevac","ror":"https://ror.org/04f7vj627","country_code":"RS","type":"education","lineage":["https://openalex.org/I14245010"]}],"countries":["RS"],"is_corresponding":false,"raw_author_name":"Yang Li","raw_affiliation_strings":["Faculty of Technical Sciences, University of Kragujevac, &#x010C;a&#x010D;ak, Serbia"],"raw_orcid":"https://orcid.org/0000-0002-8372-1481","affiliations":[{"raw_affiliation_string":"Faculty of Technical Sciences, University of Kragujevac, &#x010C;a&#x010D;ak, Serbia","institution_ids":["https://openalex.org/I14245010"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Mladenovic Vladimir","orcid":"https://orcid.org/0000-0001-8530-2312"},"institutions":[{"id":"https://openalex.org/I3045169105","display_name":"Southern University of Science and Technology","ror":"https://ror.org/049tv2d57","country_code":"CN","type":"education","lineage":["https://openalex.org/I3045169105"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Mladenovic Vladimir","raw_affiliation_strings":["Department of Electrical and Electronic Engineering, Southern University of Science and Technology, Shenzhen, China"],"raw_orcid":"https://orcid.org/0000-0001-8530-2312","affiliations":[{"raw_affiliation_string":"Department of Electrical and Electronic Engineering, Southern University of Science and Technology, Shenzhen, China","institution_ids":["https://openalex.org/I3045169105"]}]},{"author_position":"last","author":{"id":null,"display_name":"Zhihai He","orcid":"https://orcid.org/0000-0003-2255-4293"},"institutions":[{"id":"https://openalex.org/I4210136793","display_name":"Peng Cheng Laboratory","ror":"https://ror.org/03qdqbt06","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210136793"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhihai He","raw_affiliation_strings":["Pengcheng Lab, Shenzhen, China"],"raw_orcid":"https://orcid.org/0000-0003-2255-4293","affiliations":[{"raw_affiliation_string":"Pengcheng Lab, Shenzhen, China","institution_ids":["https://openalex.org/I4210136793"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.1534,"has_fulltext":false,"cited_by_count":24,"citation_normalized_percentile":{"value":0.88666122,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":"31","issue":null,"first_page":"2988","last_page":"3003"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11714","display_name":"Multimodal Machine Learning Applications","score":0.2003999948501587,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.2003999948501587,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.15950000286102295,"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"}},{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.14350000023841858,"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/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.7699000239372253},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.7080000042915344},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.6517000198364258},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.6166999936103821},{"id":"https://openalex.org/keywords/correlation","display_name":"Correlation","score":0.6065000295639038},{"id":"https://openalex.org/keywords/image-retrieval","display_name":"Image retrieval","score":0.5738000273704529},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5138000249862671},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4984999895095825},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.42089998722076416}],"concepts":[{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.7699000239372253},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7310000061988831},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.7080000042915344},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6711999773979187},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.6517000198364258},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.6166999936103821},{"id":"https://openalex.org/C117220453","wikidata":"https://www.wikidata.org/wiki/Q5172842","display_name":"Correlation","level":2,"score":0.6065000295639038},{"id":"https://openalex.org/C1667742","wikidata":"https://www.wikidata.org/wiki/Q10927554","display_name":"Image retrieval","level":3,"score":0.5738000273704529},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5138000249862671},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4984999895095825},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.42089998722076416},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.41280001401901245},{"id":"https://openalex.org/C75564084","wikidata":"https://www.wikidata.org/wiki/Q5597085","display_name":"Graph embedding","level":3,"score":0.39250001311302185},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.3781000077724457},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3659999966621399},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.33889999985694885},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.32850000262260437},{"id":"https://openalex.org/C88230418","wikidata":"https://www.wikidata.org/wiki/Q131476","display_name":"Graph theory","level":2,"score":0.3124000132083893},{"id":"https://openalex.org/C189391414","wikidata":"https://www.wikidata.org/wiki/Q7936579","display_name":"Visual Word","level":4,"score":0.30869999527931213},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.29319998621940613},{"id":"https://openalex.org/C2781122975","wikidata":"https://www.wikidata.org/wiki/Q16928266","display_name":"Semantic feature","level":2,"score":0.2922999858856201},{"id":"https://openalex.org/C2780052074","wikidata":"https://www.wikidata.org/wiki/Q1128648","display_name":"Content-based image retrieval","level":4,"score":0.28029999136924744},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.26919999718666077},{"id":"https://openalex.org/C126422989","wikidata":"https://www.wikidata.org/wiki/Q93586","display_name":"Feature detection (computer vision)","level":4,"score":0.2563000023365021}],"mesh":[{"descriptor_ui":"D012660","descriptor_name":"Semantics","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D012660","descriptor_name":"Semantics","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D012660","descriptor_name":"Semantics","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true}],"locations_count":2,"locations":[{"id":"doi:10.1109/tip.2022.3163571","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2022.3163571","pdf_url":null,"source":{"id":"https://openalex.org/S4210173141","display_name":"IEEE Transactions on Image Processing","issn_l":"1057-7149","issn":["1057-7149","1941-0042"],"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 Image Processing","raw_type":"journal-article"},{"id":"pmid:35380963","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/35380963","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 image processing : a publication of the IEEE Signal Processing Society","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1096815532","display_name":null,"funder_award_id":"451-08-1201/2021-09","funder_id":"https://openalex.org/F4320322729","funder_display_name":"Ministarstvo Prosvete, Nauke i Tehnolo\u0161kog Razvoja"},{"id":"https://openalex.org/G1447168351","display_name":null,"funder_award_id":"62011530042","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G1859168551","display_name":null,"funder_award_id":"2021YFE0110500","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"},{"id":"https://openalex.org/G386497372","display_name":null,"funder_award_id":"62062021","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4516259856","display_name":null,"funder_award_id":"2021YJS025","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"},{"id":"https://openalex.org/G7615460283","display_name":"\u9762\u5411\u76d1\u63a7\u89c6\u9891\u7684\u7ed3\u6784\u5316\u6df1\u5ea6\u7279\u5f81\u878d\u5408\u76ee\u6807\u91cd\u8bc6\u522b\u7814\u7a76","funder_award_id":"61872034","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8764725052","display_name":null,"funder_award_id":"4202055","funder_id":"https://openalex.org/F4320334977","funder_display_name":"Beijing Municipal Natural Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320322729","display_name":"Ministarstvo Prosvete, Nauke i Tehnolo\u0161kog Razvoja","ror":"https://ror.org/01znas443"},{"id":"https://openalex.org/F4320334977","display_name":"Beijing Municipal Natural Science Foundation","ror":null},{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null},{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":59,"referenced_works":["https://openalex.org/W1875842236","https://openalex.org/W2021354639","https://openalex.org/W2023991840","https://openalex.org/W2096733369","https://openalex.org/W2097117768","https://openalex.org/W2124509324","https://openalex.org/W2138011018","https://openalex.org/W2138621090","https://openalex.org/W2155893237","https://openalex.org/W2194775991","https://openalex.org/W2204750386","https://openalex.org/W2470322391","https://openalex.org/W2471768434","https://openalex.org/W2605102252","https://openalex.org/W2613997951","https://openalex.org/W2741307002","https://openalex.org/W2746265758","https://openalex.org/W2914050157","https://openalex.org/W2917267381","https://openalex.org/W2921310091","https://openalex.org/W2943605315","https://openalex.org/W2948077755","https://openalex.org/W2948303601","https://openalex.org/W2948638722","https://openalex.org/W2953271441","https://openalex.org/W2963026686","https://openalex.org/W2963113119","https://openalex.org/W2963469388","https://openalex.org/W2963713828","https://openalex.org/W2964117779","https://openalex.org/W2964231884","https://openalex.org/W2964271799","https://openalex.org/W2965744772","https://openalex.org/W2979300990","https://openalex.org/W2981015789","https://openalex.org/W2982112268","https://openalex.org/W2987852271","https://openalex.org/W2988281744","https://openalex.org/W2991234496","https://openalex.org/W2991581349","https://openalex.org/W2991642706","https://openalex.org/W2991645104","https://openalex.org/W2998702515","https://openalex.org/W3034202663","https://openalex.org/W3034303554","https://openalex.org/W3035014997","https://openalex.org/W3035194537","https://openalex.org/W3035295689","https://openalex.org/W3035524453","https://openalex.org/W3035748723","https://openalex.org/W3098087652","https://openalex.org/W3106778652","https://openalex.org/W3152893301","https://openalex.org/W3175616662","https://openalex.org/W4213009331","https://openalex.org/W6638667902","https://openalex.org/W6729100687","https://openalex.org/W6729265172","https://openalex.org/W6787972765"],"related_works":["https://openalex.org/W2743258233","https://openalex.org/W2970216048","https://openalex.org/W2586441539","https://openalex.org/W2136516428","https://openalex.org/W2806866760","https://openalex.org/W2905846897","https://openalex.org/W2005051400","https://openalex.org/W4225789408","https://openalex.org/W3016451726","https://openalex.org/W4226204352"],"abstract_inverted_index":{"Deep":[0],"feature":[1,9,53,73,117,124],"embedding":[2,118],"aims":[3],"to":[4,46,51,61,86,105,120],"learn":[5,56,100,115],"discriminative":[6],"features":[7,92,137],"or":[8],"embeddings":[10],"for":[11,125,167],"image":[12,128,136,150],"samples":[13],"which":[14],"can":[15],"minimize":[16],"their":[17,22,90],"intra-class":[18],"distance":[19],"while":[20],"maximizing":[21],"inter-class":[23],"distance.":[24],"Recent":[25],"state-of-the-art":[26,160],"methods":[27,161],"have":[28],"been":[29],"focusing":[30],"on":[31,76,94,130],"learning":[32],"deep":[33,52],"neural":[34,59],"networks":[35],"with":[36,83,138],"carefully":[37],"designed":[38],"loss":[39],"functions.":[40],"In":[41],"this":[42,77],"work,":[43],"we":[44],"propose":[45],"explore":[47],"a":[48,57,101,116,126,131,163],"new":[49],"approach":[50],"embedding.":[54],"We":[55],"graph":[58],"network":[60,104,119],"characterize":[62],"and":[63,88],"predict":[64,106],"the":[65,72,107,122,139,149,159],"local":[66,95],"correlation":[67,78,102,108,140],"structure":[68],"of":[69,134],"images":[70,81],"in":[71],"space.":[74],"Based":[75],"structure,":[79],"neighboring":[80,111,135],"collaborate":[82],"each":[84],"other":[85],"generate":[87,121],"refine":[89],"embedded":[91,123],"based":[93,129],"linear":[96],"combination.":[97],"Graph":[98,113],"edges":[99],"prediction":[103],"scores":[109,141],"between":[110],"images.":[112],"nodes":[114],"given":[127],"weighted":[132],"summation":[133],"as":[142],"weights.":[143],"Our":[144],"extensive":[145],"experimental":[146],"results":[147],"under":[148],"retrieval":[151],"settings":[152],"demonstrate":[153],"that":[154],"our":[155],"proposed":[156],"method":[157],"outperforms":[158],"by":[162],"large":[164],"margin,":[165],"especially":[166],"top-1":[168],"recalls.":[169]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":7},{"year":2022,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2022-05-05T00:00:00"}
