{"id":"https://openalex.org/W3195845222","doi":"https://doi.org/10.1109/tip.2021.3104192","title":"Kinship Verification Based on Cross-Generation Feature Interaction Learning","display_name":"Kinship Verification Based on Cross-Generation Feature Interaction Learning","publication_year":2021,"publication_date":"2021-01-01","ids":{"openalex":"https://openalex.org/W3195845222","doi":"https://doi.org/10.1109/tip.2021.3104192","mag":"3195845222","pmid":"https://pubmed.ncbi.nlm.nih.gov/34415834"},"language":"en","primary_location":{"id":"doi:10.1109/tip.2021.3104192","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2021.3104192","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":["arxiv","crossref","pubmed"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2109.02809","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Guan-Nan Dong","orcid":"https://orcid.org/0000-0002-1919-3258"},"institutions":[{"id":"https://openalex.org/I204512498","display_name":"University of Macau","ror":"https://ror.org/01r4q9n85","country_code":"MO","type":"education","lineage":["https://openalex.org/I204512498"]}],"countries":["MO"],"is_corresponding":false,"raw_author_name":"Guan-Nan Dong","raw_affiliation_strings":["Department of Computer and Information Science, University of Macau, Macau"],"raw_orcid":"https://orcid.org/0000-0002-1919-3258","affiliations":[{"raw_affiliation_string":"Department of Computer and Information Science, University of Macau, Macau","institution_ids":["https://openalex.org/I204512498"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Chi-Man Pun","orcid":"https://orcid.org/0000-0003-1788-3746"},"institutions":[{"id":"https://openalex.org/I204512498","display_name":"University of Macau","ror":"https://ror.org/01r4q9n85","country_code":"MO","type":"education","lineage":["https://openalex.org/I204512498"]}],"countries":["MO"],"is_corresponding":false,"raw_author_name":"Chi-Man Pun","raw_affiliation_strings":["Department of Computer and Information Science, University of Macau, Macau"],"raw_orcid":"https://orcid.org/0000-0003-1788-3746","affiliations":[{"raw_affiliation_string":"Department of Computer and Information Science, University of Macau, Macau","institution_ids":["https://openalex.org/I204512498"]}]},{"author_position":"last","author":{"id":null,"display_name":"Zheng Zhang","orcid":"https://orcid.org/0000-0003-1470-6998"},"institutions":[{"id":"https://openalex.org/I204512498","display_name":"University of Macau","ror":"https://ror.org/01r4q9n85","country_code":"MO","type":"education","lineage":["https://openalex.org/I204512498"]}],"countries":["MO"],"is_corresponding":false,"raw_author_name":"Zheng Zhang","raw_affiliation_strings":["Department of Computer and Information Science, University of Macau, Macau"],"raw_orcid":"https://orcid.org/0000-0003-1470-6998","affiliations":[{"raw_affiliation_string":"Department of Computer and Information Science, University of Macau, Macau","institution_ids":["https://openalex.org/I204512498"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I204512498"],"apc_list":null,"apc_paid":null,"fwci":0.6328,"has_fulltext":false,"cited_by_count":13,"citation_normalized_percentile":{"value":0.66285141,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"30","issue":null,"first_page":"7391","last_page":"7403"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11448","display_name":"Face recognition and analysis","score":0.9677000045776367,"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/T11448","display_name":"Face recognition and analysis","score":0.9677000045776367,"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/T11118","display_name":"Evolutionary Psychology and Human Behavior","score":0.007600000128149986,"subfield":{"id":"https://openalex.org/subfields/3205","display_name":"Experimental and Cognitive Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10828","display_name":"Biometric Identification and Security","score":0.006099999882280827,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/similarity","display_name":"Similarity (geometry)","score":0.7314000129699707},{"id":"https://openalex.org/keywords/weighting","display_name":"Weighting","score":0.6672000288963318},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6334999799728394},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.6316999793052673},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.6010000109672546},{"id":"https://openalex.org/keywords/semantics","display_name":"Semantics (computer science)","score":0.5651000142097473},{"id":"https://openalex.org/keywords/kinship","display_name":"Kinship","score":0.5282999873161316},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.37049999833106995}],"concepts":[{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.7314000129699707},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7145000100135803},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6934999823570251},{"id":"https://openalex.org/C183115368","wikidata":"https://www.wikidata.org/wiki/Q856577","display_name":"Weighting","level":2,"score":0.6672000288963318},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6334999799728394},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.6316999793052673},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.6010000109672546},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.5651000142097473},{"id":"https://openalex.org/C144348335","wikidata":"https://www.wikidata.org/wiki/Q171318","display_name":"Kinship","level":2,"score":0.5282999873161316},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.37049999833106995},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.36809998750686646},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.366100013256073},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.3596999943256378},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3312000036239624},{"id":"https://openalex.org/C130318100","wikidata":"https://www.wikidata.org/wiki/Q2268914","display_name":"Semantic similarity","level":2,"score":0.3142000138759613},{"id":"https://openalex.org/C143271835","wikidata":"https://www.wikidata.org/wiki/Q254515","display_name":"Similitude","level":2,"score":0.3059000074863434},{"id":"https://openalex.org/C31510193","wikidata":"https://www.wikidata.org/wiki/Q1192553","display_name":"Facial recognition system","level":3,"score":0.3050999939441681},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.30149999260902405},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.2994999885559082},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.2799000144004822},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.27720001339912415},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.2563999891281128},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.2540000081062317}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/tip.2021.3104192","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2021.3104192","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:34415834","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/34415834","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},{"id":"pmh:oai:arXiv.org:2109.02809","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2109.02809","pdf_url":"https://arxiv.org/pdf/2109.02809","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2109.02809","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2109.02809","pdf_url":"https://arxiv.org/pdf/2109.02809","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2603898597","display_name":null,"funder_award_id":"MYRG2019-00086-FST","funder_id":"https://openalex.org/F4320322841","funder_display_name":"Universidade de Macau"},{"id":"https://openalex.org/G6702671400","display_name":null,"funder_award_id":"MYRG2018-00035-FST","funder_id":"https://openalex.org/F4320322841","funder_display_name":"Universidade de Macau"}],"funders":[{"id":"https://openalex.org/F4320322841","display_name":"Universidade de Macau","ror":"https://ror.org/01r4q9n85"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":58,"referenced_works":["https://openalex.org/W1185609327","https://openalex.org/W1498305593","https://openalex.org/W1996337501","https://openalex.org/W2001141328","https://openalex.org/W2012783213","https://openalex.org/W2053186076","https://openalex.org/W2096733369","https://openalex.org/W2097073572","https://openalex.org/W2097308346","https://openalex.org/W2108598243","https://openalex.org/W2108909793","https://openalex.org/W2122111042","https://openalex.org/W2132886138","https://openalex.org/W2144935315","https://openalex.org/W2145773134","https://openalex.org/W2157364932","https://openalex.org/W2161969291","https://openalex.org/W2163808566","https://openalex.org/W2169495281","https://openalex.org/W2184983556","https://openalex.org/W2194775991","https://openalex.org/W2323476717","https://openalex.org/W2341528187","https://openalex.org/W2343020623","https://openalex.org/W2505321620","https://openalex.org/W2515880331","https://openalex.org/W2520903215","https://openalex.org/W2560852071","https://openalex.org/W2592683830","https://openalex.org/W2679426462","https://openalex.org/W2725177198","https://openalex.org/W2766233005","https://openalex.org/W2766372859","https://openalex.org/W2769490994","https://openalex.org/W2770681586","https://openalex.org/W2797200251","https://openalex.org/W2804093170","https://openalex.org/W2896441583","https://openalex.org/W2897151190","https://openalex.org/W2938731855","https://openalex.org/W2963026686","https://openalex.org/W2963940609","https://openalex.org/W2963988212","https://openalex.org/W2970933349","https://openalex.org/W2980642884","https://openalex.org/W3012957270","https://openalex.org/W3034668985","https://openalex.org/W3034773849","https://openalex.org/W4297849620","https://openalex.org/W6602994362","https://openalex.org/W6637373629","https://openalex.org/W6675751002","https://openalex.org/W6677328822","https://openalex.org/W6681239517","https://openalex.org/W6681440187","https://openalex.org/W6726946684","https://openalex.org/W6730323794","https://openalex.org/W6766667439"],"related_works":[],"abstract_inverted_index":{"Kinship":[0],"verification":[1,207],"from":[2,81,169,188],"facial":[3],"images":[4,182],"has":[5],"been":[6],"recognized":[7],"as":[8,69,94],"an":[9,38],"emerging":[10],"yet":[11],"challenging":[12],"technique":[13],"in":[14,181],"many":[15],"potential":[16],"computer":[17],"vision":[18],"applications.":[19],"In":[20],"this":[21],"paper,":[22],"we":[23,64,89,153],"propose":[24],"a":[25,70],"novel":[26],"cross-generation":[27,50],"feature":[28,151,158],"interaction":[29],"learning":[30,156,163],"(CFIL)":[31],"framework":[32],"for":[33],"robust":[34],"kinship":[35,206],"verification.":[36],"Particularly,":[37],"effective":[39],"collaborative":[40],"weighting":[41],"strategy":[42],"is":[43],"constructed":[44],"to":[45,72,104,203],"explore":[46],"the":[47,74,82,91,95,100,106,123,177,194,199],"characteristics":[48],"of":[49,56,140,145,198],"relations":[51],"by":[52,87,135],"corporately":[53],"extracting":[54],"features":[55,132,173],"both":[57],"parents":[58,66],"and":[59,67,77,108,130,150,157,171,183,196],"children":[60,68],"image":[61,189],"pairs.":[62,190],"Specifically,":[63],"take":[65],"whole":[71,107],"extract":[73],"expressive":[75],"local":[76,129,170],"non-local":[78,131,172],"features.":[79,110],"Different":[80],"traditional":[83],"works":[84],"measuring":[85],"similarity":[86,92,112,148,155],"distance,":[88],"interpolate":[90],"calculations":[93],"interior":[96],"auxiliary":[97],"weights":[98,113],"into":[99,160],"deep":[101],"CNN":[102],"architecture":[103],"learn":[105],"natural":[109],"These":[111],"not":[114],"only":[115],"involve":[116],"corresponding":[117],"single":[118],"points":[119],"but":[120],"also":[121],"excavate":[122],"multiple":[124],"relationships":[125],"cross":[126],"points,":[127],"where":[128],"are":[133],"calculated":[134],"using":[136],"these":[137],"two":[138],"kinds":[139],"distance":[141],"measurements.":[142],"Importantly,":[143],"instead":[144],"separately":[146],"conducting":[147],"computation":[149],"extraction,":[152],"integrate":[154],"extraction":[159],"one":[161],"unified":[162],"process.":[164],"The":[165],"integrated":[166],"representations":[167],"deduced":[168],"can":[174],"comprehensively":[175],"express":[176],"informative":[178],"semantics":[179],"embedded":[180],"preserve":[184],"abundant":[185],"correlation":[186],"knowledge":[187],"Extensive":[191],"experiments":[192],"demonstrate":[193],"efficiency":[195],"superiority":[197],"proposed":[200],"model":[201],"compared":[202],"some":[204],"state-of-the-art":[205],"methods.":[208]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":1}],"updated_date":"2026-07-15T18:14:33.161393","created_date":"2021-08-30T00:00:00"}
