{"id":"https://openalex.org/W4367556650","doi":"https://doi.org/10.1587/transinf.2022edp7163","title":"Learning Local Similarity with Spatial Interrelations on Content-Based Image Retrieval","display_name":"Learning Local Similarity with Spatial Interrelations on Content-Based Image Retrieval","publication_year":2023,"publication_date":"2023-04-30","ids":{"openalex":"https://openalex.org/W4367556650","doi":"https://doi.org/10.1587/transinf.2022edp7163"},"language":"en","primary_location":{"id":"doi:10.1587/transinf.2022edp7163","is_oa":true,"landing_page_url":"https://doi.org/10.1587/transinf.2022edp7163","pdf_url":"https://www.jstage.jst.go.jp/article/transinf/E106.D/5/E106.D_2022EDP7163/_pdf","source":{"id":"https://openalex.org/S2486202937","display_name":"IEICE Transactions on Information and Systems","issn_l":"0916-8532","issn":["0916-8532","1745-1361"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4320800604","host_organization_name":"Institute of Electronics, Information and Communication Engineers","host_organization_lineage":["https://openalex.org/P4320800604"],"host_organization_lineage_names":["Institute of Electronics, Information and Communication Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEICE Transactions on Information and Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://www.jstage.jst.go.jp/article/transinf/E106.D/5/E106.D_2022EDP7163/_pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5062348639","display_name":"Longjiao Zhao","orcid":null},"institutions":[{"id":"https://openalex.org/I60134161","display_name":"Nagoya University","ror":"https://ror.org/04chrp450","country_code":"JP","type":"education","lineage":["https://openalex.org/I60134161"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Longjiao ZHAO","raw_affiliation_strings":["Graduate School of Informatics, Nagoya University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Graduate School of Informatics, Nagoya University","institution_ids":["https://openalex.org/I60134161"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100445098","display_name":"Yu Wang","orcid":"https://orcid.org/0000-0001-7959-3387"},"institutions":[{"id":"https://openalex.org/I111428342","display_name":"Hitotsubashi University","ror":"https://ror.org/04jqj7p05","country_code":"JP","type":"education","lineage":["https://openalex.org/I111428342"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Yu WANG","raw_affiliation_strings":["Center for Information and Communication Technology, Hitotsubashi University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Center for Information and Communication Technology, Hitotsubashi University","institution_ids":["https://openalex.org/I111428342"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5080180020","display_name":"Jien Kato","orcid":"https://orcid.org/0000-0002-0196-4405"},"institutions":[{"id":"https://openalex.org/I135768898","display_name":"Ritsumeikan University","ror":"https://ror.org/0197nmd03","country_code":"JP","type":"education","lineage":["https://openalex.org/I135768898","https://openalex.org/I4390039241"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Jien KATO","raw_affiliation_strings":["College of Information Science and Engineering, Ritsumeikan University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Information Science and Engineering, Ritsumeikan University","institution_ids":["https://openalex.org/I135768898"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5009095770","display_name":"Yoshiharu ISHIKAWA","orcid":null},"institutions":[{"id":"https://openalex.org/I60134161","display_name":"Nagoya University","ror":"https://ror.org/04chrp450","country_code":"JP","type":"education","lineage":["https://openalex.org/I60134161"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Yoshiharu ISHIKAWA","raw_affiliation_strings":["Graduate School of Informatics, Nagoya University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Graduate School of Informatics, Nagoya University","institution_ids":["https://openalex.org/I60134161"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.2127,"has_fulltext":true,"cited_by_count":2,"citation_normalized_percentile":{"value":0.46464864,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":96},"biblio":{"volume":"E106.D","issue":"5","first_page":"1069","last_page":"1080"},"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":0.9997000098228455,"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":0.9991999864578247,"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/pooling","display_name":"Pooling","score":0.9065679311752319},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8174149990081787},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.7275166511535645},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6602377891540527},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.652015745639801},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6358935236930847},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.5235490202903748},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.331692636013031},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.31414198875427246}],"concepts":[{"id":"https://openalex.org/C70437156","wikidata":"https://www.wikidata.org/wiki/Q7228652","display_name":"Pooling","level":2,"score":0.9065679311752319},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8174149990081787},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.7275166511535645},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6602377891540527},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.652015745639801},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6358935236930847},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.5235490202903748},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.331692636013031},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.31414198875427246},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1587/transinf.2022edp7163","is_oa":true,"landing_page_url":"https://doi.org/10.1587/transinf.2022edp7163","pdf_url":"https://www.jstage.jst.go.jp/article/transinf/E106.D/5/E106.D_2022EDP7163/_pdf","source":{"id":"https://openalex.org/S2486202937","display_name":"IEICE Transactions on Information and Systems","issn_l":"0916-8532","issn":["0916-8532","1745-1361"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4320800604","host_organization_name":"Institute of Electronics, Information and Communication Engineers","host_organization_lineage":["https://openalex.org/P4320800604"],"host_organization_lineage_names":["Institute of Electronics, Information and Communication Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEICE Transactions on Information and Systems","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1587/transinf.2022edp7163","is_oa":true,"landing_page_url":"https://doi.org/10.1587/transinf.2022edp7163","pdf_url":"https://www.jstage.jst.go.jp/article/transinf/E106.D/5/E106.D_2022EDP7163/_pdf","source":{"id":"https://openalex.org/S2486202937","display_name":"IEICE Transactions on Information and Systems","issn_l":"0916-8532","issn":["0916-8532","1745-1361"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4320800604","host_organization_name":"Institute of Electronics, Information and Communication Engineers","host_organization_lineage":["https://openalex.org/P4320800604"],"host_organization_lineage_names":["Institute of Electronics, Information and Communication Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEICE Transactions on Information and Systems","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Reduced inequalities","score":0.5199999809265137,"id":"https://metadata.un.org/sdg/10"},{"display_name":"Peace, Justice and strong institutions","score":0.46000000834465027,"id":"https://metadata.un.org/sdg/16"}],"awards":[{"id":"https://openalex.org/G5390586714","display_name":"High Risk Pedestrian Detection for Early Danger Avoidance","funder_award_id":"22K12103","funder_id":"https://openalex.org/F4320334764","funder_display_name":"Japan Society for the Promotion of Science"}],"funders":[{"id":"https://openalex.org/F4320334764","display_name":"Japan Society for the Promotion of Science","ror":"https://ror.org/00hhkn466"}],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4367556650.pdf"},"referenced_works_count":42,"referenced_works":["https://openalex.org/W204268067","https://openalex.org/W1524680991","https://openalex.org/W1606858007","https://openalex.org/W1686810756","https://openalex.org/W1849277567","https://openalex.org/W1984309565","https://openalex.org/W2046589280","https://openalex.org/W2095569536","https://openalex.org/W2099987538","https://openalex.org/W2101498401","https://openalex.org/W2124386111","https://openalex.org/W2130660124","https://openalex.org/W2131846894","https://openalex.org/W2141362318","https://openalex.org/W2147069236","https://openalex.org/W2148809531","https://openalex.org/W2161969291","https://openalex.org/W2163605009","https://openalex.org/W2174726731","https://openalex.org/W2194775991","https://openalex.org/W2204975001","https://openalex.org/W2295107390","https://openalex.org/W2295537791","https://openalex.org/W2340690086","https://openalex.org/W2583409994","https://openalex.org/W2751825910","https://openalex.org/W2773163206","https://openalex.org/W2803163484","https://openalex.org/W2951019013","https://openalex.org/W2962858109","https://openalex.org/W2962941391","https://openalex.org/W2963125676","https://openalex.org/W2963129433","https://openalex.org/W2963436667","https://openalex.org/W2963446712","https://openalex.org/W2963588253","https://openalex.org/W2970971581","https://openalex.org/W2981398794","https://openalex.org/W3006408808","https://openalex.org/W3110536152","https://openalex.org/W3173736705","https://openalex.org/W3188851454"],"related_works":["https://openalex.org/W2792080776","https://openalex.org/W2943085063","https://openalex.org/W3172946746","https://openalex.org/W2514274290","https://openalex.org/W2517027266","https://openalex.org/W2424871898","https://openalex.org/W2291847203","https://openalex.org/W2758063741","https://openalex.org/W2940661641","https://openalex.org/W2969680539"],"abstract_inverted_index":{"Convolutional":[0],"Neural":[1],"Networks":[2],"(CNNs)":[3],"have":[4],"recently":[5],"demonstrated":[6],"outstanding":[7],"performance":[8],"in":[9,19,24,28],"image":[10],"retrieval":[11,209],"tasks.":[12],"Local":[13],"convolutional":[14,100],"features":[15,39,42],"extracted":[16],"by":[17,96],"CNNs,":[18],"particular,":[20],"show":[21],"exceptional":[22],"capability":[23],"discrimination.":[25],"Recent":[26],"research":[27],"this":[29,80],"field":[30],"has":[31],"concentrated":[32],"on":[33,92,137,178,206],"pooling":[34,53,84,198,217],"methods":[35,54,199,218],"that":[36,192,212],"incorporate":[37],"local":[38,58,93,99,109,119,163,166,173],"into":[40,115],"global":[41,46],"and":[43,61,76,146,169],"assess":[44,140],"the":[45,52,56,69,72,141,144,193,197,220],"similarity":[47,110,132,142],"of":[48,83,108,152,201],"two":[49],"images.":[50,148],"However,":[51],"sacrifice":[55],"image's":[57],"region":[59,164,167],"information":[60,117],"spatial":[62,124,170],"relationships,":[63],"which":[64,113],"are":[65,186],"precisely":[66],"known":[67],"as":[68,121,123],"keys":[70],"to":[71,139,188],"robustness":[73,202],"against":[74],"occlusion":[75],"viewpoint":[77],"changes.":[78],"In":[79],"paper,":[81],"instead":[82],"methods,":[85],"we":[86,103],"propose":[87],"an":[88],"alternative":[89],"method":[90,154,195],"based":[91,136],"similarity,":[94],"determined":[95],"directly":[97],"using":[98],"features.":[101],"Specifically,":[102],"first":[104],"define":[105],"three":[106,161,207],"forms":[107],"tensors":[111],"(LSTs),":[112],"take":[114],"account":[116],"about":[118],"regions":[120],"well":[122],"relationships":[125,171],"between":[126,143,172],"them.":[127],"We":[128],"then":[129],"construct":[130],"a":[131,179],"CNN":[133],"model":[134],"(SCNN)":[135],"LSTs":[138,214],"query":[145,184],"gallery":[147],"The":[149,175],"ideal":[150],"configuration":[151],"our":[153],"is":[155],"sought":[156],"through":[157],"thorough":[158],"experiments":[159],"from":[160],"perspectives:":[162],"size,":[165],"content,":[168],"regions.":[174],"experimental":[176],"results":[177],"modified":[180],"open":[181],"dataset":[182],"(where":[183],"images":[185],"limited":[187],"occluded":[189],"ones)":[190],"confirm":[191],"proposed":[194],"outperforms":[196],"because":[200],"enhancement.":[203],"Furthermore,":[204],"testing":[205],"public":[208],"datasets":[210],"shows":[211],"combining":[213],"with":[215],"conventional":[216],"achieves":[219],"best":[221],"results.":[222]},"counts_by_year":[{"year":2025,"cited_by_count":2}],"updated_date":"2025-12-24T23:09:58.560324","created_date":"2025-10-10T00:00:00"}