{"id":"https://openalex.org/W4306832756","doi":"https://doi.org/10.1109/tip.2022.3214092","title":"Middle-Level Feature Fusion for Lightweight RGB-D Salient Object Detection","display_name":"Middle-Level Feature Fusion for Lightweight RGB-D Salient Object Detection","publication_year":2022,"publication_date":"2022-01-01","ids":{"openalex":"https://openalex.org/W4306832756","doi":"https://doi.org/10.1109/tip.2022.3214092","pmid":"https://pubmed.ncbi.nlm.nih.gov/36256711"},"language":"en","primary_location":{"id":"doi:10.1109/tip.2022.3214092","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2022.3214092","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":true,"oa_status":"green","oa_url":"https://pure.aber.ac.uk/portal/en/publications/middlelevel-feature-fusion-for-lightweight-rgbd-salient-object-detection(9a31af98-d834-4531-bcd9-b9c6ceb6b349).html","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5083599023","display_name":"Nianchang Huang","orcid":"https://orcid.org/0000-0001-9530-3490"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Nianchang Huang","raw_affiliation_strings":["Key Laboratory of Electronic Equipment Structure Design, Ministry of Education, and the Center for Complex Systems, School of Mechano-Electronic Engineering, Xidian University, Xi&#x2019;an, Shaanxi, China"],"affiliations":[{"raw_affiliation_string":"Key Laboratory of Electronic Equipment Structure Design, Ministry of Education, and the Center for Complex Systems, School of Mechano-Electronic Engineering, Xidian University, Xi&#x2019;an, Shaanxi, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5028921727","display_name":"Qiang Jiao","orcid":"https://orcid.org/0000-0002-4725-5284"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qiang Jiao","raw_affiliation_strings":["Key Laboratory of Electronic Equipment Structure Design, Ministry of Education, and the Center for Complex Systems, School of Mechano-Electronic Engineering, Xidian University, Xi&#x2019;an, Shaanxi, China"],"affiliations":[{"raw_affiliation_string":"Key Laboratory of Electronic Equipment Structure Design, Ministry of Education, and the Center for Complex Systems, School of Mechano-Electronic Engineering, Xidian University, Xi&#x2019;an, Shaanxi, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100381904","display_name":"Qiang Zhang","orcid":"https://orcid.org/0000-0002-2828-9905"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qiang Zhang","raw_affiliation_strings":["Key Laboratory of Electronic Equipment Structure Design, Ministry of Education, and the Center for Complex Systems, School of Mechano-Electronic Engineering, Xidian University, Xi&#x2019;an, Shaanxi, China"],"affiliations":[{"raw_affiliation_string":"Key Laboratory of Electronic Equipment Structure Design, Ministry of Education, and the Center for Complex Systems, School of Mechano-Electronic Engineering, Xidian University, Xi&#x2019;an, Shaanxi, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5046605531","display_name":"Jungong Han","orcid":"https://orcid.org/0000-0003-4361-956X"},"institutions":[{"id":"https://openalex.org/I16038530","display_name":"Aberystwyth University","ror":"https://ror.org/015m2p889","country_code":"GB","type":"education","lineage":["https://openalex.org/I16038530"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Jungong Han","raw_affiliation_strings":["Computer Science Department, Aberystwyth University, Aberystwyth, U.K"],"affiliations":[{"raw_affiliation_string":"Computer Science Department, Aberystwyth University, Aberystwyth, U.K","institution_ids":["https://openalex.org/I16038530"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5083599023"],"corresponding_institution_ids":["https://openalex.org/I149594827"],"apc_list":null,"apc_paid":null,"fwci":4.5848,"has_fulltext":false,"cited_by_count":50,"citation_normalized_percentile":{"value":0.96,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":"31","issue":null,"first_page":"6621","last_page":"6634"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11605","display_name":"Visual Attention and Saliency Detection","score":1.0,"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/T11605","display_name":"Visual Attention and Saliency Detection","score":1.0,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9754999876022339,"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/T11094","display_name":"Face Recognition and Perception","score":0.9660999774932861,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6892537474632263},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6639134883880615},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.6423025131225586},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.6290218234062195},{"id":"https://openalex.org/keywords/rgb-color-model","display_name":"RGB color model","score":0.6267298460006714},{"id":"https://openalex.org/keywords/modal","display_name":"Modal","score":0.6254662275314331},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6048507690429688},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.6034348607063293},{"id":"https://openalex.org/keywords/subnetwork","display_name":"Subnetwork","score":0.530788779258728},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.48732051253318787},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4637148380279541},{"id":"https://openalex.org/keywords/fuse","display_name":"Fuse (electrical)","score":0.44576138257980347},{"id":"https://openalex.org/keywords/fusion","display_name":"Fusion","score":0.4289751648902893},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.1314629316329956}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6892537474632263},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6639134883880615},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.6423025131225586},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.6290218234062195},{"id":"https://openalex.org/C82990744","wikidata":"https://www.wikidata.org/wiki/Q166194","display_name":"RGB color model","level":2,"score":0.6267298460006714},{"id":"https://openalex.org/C71139939","wikidata":"https://www.wikidata.org/wiki/Q910194","display_name":"Modal","level":2,"score":0.6254662275314331},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6048507690429688},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.6034348607063293},{"id":"https://openalex.org/C2780186347","wikidata":"https://www.wikidata.org/wiki/Q11414","display_name":"Subnetwork","level":2,"score":0.530788779258728},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.48732051253318787},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4637148380279541},{"id":"https://openalex.org/C141353440","wikidata":"https://www.wikidata.org/wiki/Q182221","display_name":"Fuse (electrical)","level":2,"score":0.44576138257980347},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.4289751648902893},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.1314629316329956},{"id":"https://openalex.org/C188027245","wikidata":"https://www.wikidata.org/wiki/Q750446","display_name":"Polymer chemistry","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"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/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/tip.2022.3214092","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2022.3214092","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:36256711","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/36256711","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:aber.ac.uk:publications/9a31af98-d834-4531-bcd9-b9c6ceb6b349","is_oa":true,"landing_page_url":"https://pure.aber.ac.uk/portal/en/publications/middlelevel-feature-fusion-for-lightweight-rgbd-salient-object-detection(9a31af98-d834-4531-bcd9-b9c6ceb6b349).html","pdf_url":null,"source":{"id":"https://openalex.org/S4306401660","display_name":"Aberystwyth Research portal (Aberystwyth University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I16038530","host_organization_name":"Aberystwyth University","host_organization_lineage":["https://openalex.org/I16038530"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":""}],"best_oa_location":{"id":"pmh:oai:aber.ac.uk:publications/9a31af98-d834-4531-bcd9-b9c6ceb6b349","is_oa":true,"landing_page_url":"https://pure.aber.ac.uk/portal/en/publications/middlelevel-feature-fusion-for-lightweight-rgbd-salient-object-detection(9a31af98-d834-4531-bcd9-b9c6ceb6b349).html","pdf_url":null,"source":{"id":"https://openalex.org/S4306401660","display_name":"Aberystwyth Research portal (Aberystwyth University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I16038530","host_organization_name":"Aberystwyth University","host_organization_lineage":["https://openalex.org/I16038530"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":""},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/12","display_name":"Responsible consumption and production","score":0.49000000953674316}],"awards":[{"id":"https://openalex.org/G1074159159","display_name":null,"funder_award_id":"2019JQ-312","funder_id":"https://openalex.org/F4320324173","funder_display_name":"Natural Science Foundation of Shaanxi Province"},{"id":"https://openalex.org/G3586269372","display_name":null,"funder_award_id":"61773301","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320323230","display_name":"Xidian University","ror":"https://ror.org/05s92vm98"},{"id":"https://openalex.org/F4320324173","display_name":"Natural Science Foundation of Shaanxi Province","ror":null},{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":93,"referenced_works":["https://openalex.org/W20683899","https://openalex.org/W1686810756","https://openalex.org/W1947031653","https://openalex.org/W1976409045","https://openalex.org/W1993713494","https://openalex.org/W2085466496","https://openalex.org/W2108598243","https://openalex.org/W2128272608","https://openalex.org/W2151047074","https://openalex.org/W2160613239","https://openalex.org/W2194775991","https://openalex.org/W2517325737","https://openalex.org/W2520640394","https://openalex.org/W2569272946","https://openalex.org/W2585592883","https://openalex.org/W2607011617","https://openalex.org/W2610921592","https://openalex.org/W2624240493","https://openalex.org/W2765838470","https://openalex.org/W2796152967","https://openalex.org/W2798857366","https://openalex.org/W2804743778","https://openalex.org/W2883780447","https://openalex.org/W2887522866","https://openalex.org/W2902535732","https://openalex.org/W2909381593","https://openalex.org/W2910219960","https://openalex.org/W2913602965","https://openalex.org/W2917790938","https://openalex.org/W2921653116","https://openalex.org/W2938260698","https://openalex.org/W2939217524","https://openalex.org/W2948300571","https://openalex.org/W2948500402","https://openalex.org/W2957414648","https://openalex.org/W2962159375","https://openalex.org/W2963529609","https://openalex.org/W2963868681","https://openalex.org/W2963897031","https://openalex.org/W2964775615","https://openalex.org/W2969377765","https://openalex.org/W2981510929","https://openalex.org/W2990984982","https://openalex.org/W2999458807","https://openalex.org/W3002301267","https://openalex.org/W3003376220","https://openalex.org/W3006465601","https://openalex.org/W3008128973","https://openalex.org/W3010616503","https://openalex.org/W3010722397","https://openalex.org/W3011305844","https://openalex.org/W3022015146","https://openalex.org/W3035284915","https://openalex.org/W3035357085","https://openalex.org/W3035422681","https://openalex.org/W3035687312","https://openalex.org/W3045052737","https://openalex.org/W3097053213","https://openalex.org/W3097336090","https://openalex.org/W3097725659","https://openalex.org/W3098389804","https://openalex.org/W3099871687","https://openalex.org/W3103912303","https://openalex.org/W3106587394","https://openalex.org/W3108421143","https://openalex.org/W3108608656","https://openalex.org/W3109623941","https://openalex.org/W3112885960","https://openalex.org/W3114152269","https://openalex.org/W3114848016","https://openalex.org/W3118710621","https://openalex.org/W3120113457","https://openalex.org/W3122490299","https://openalex.org/W3127842933","https://openalex.org/W3131552587","https://openalex.org/W3134912427","https://openalex.org/W3135874576","https://openalex.org/W3140528754","https://openalex.org/W3154314696","https://openalex.org/W3206198586","https://openalex.org/W3207668590","https://openalex.org/W3208937872","https://openalex.org/W3211246039","https://openalex.org/W4205971281","https://openalex.org/W4224247218","https://openalex.org/W4224330024","https://openalex.org/W4239072543","https://openalex.org/W4285242672","https://openalex.org/W4295312788","https://openalex.org/W6631943919","https://openalex.org/W6637373629","https://openalex.org/W6766978945","https://openalex.org/W6785816937"],"related_works":["https://openalex.org/W2060724872","https://openalex.org/W2082094785","https://openalex.org/W2202198356","https://openalex.org/W3087203342","https://openalex.org/W2377184161","https://openalex.org/W228984114","https://openalex.org/W2090026684","https://openalex.org/W1971268144","https://openalex.org/W4390606538","https://openalex.org/W2095903272"],"abstract_inverted_index":{"Most":[0],"existing":[1],"RGB-D":[2,74],"salient":[3,133],"object":[4,134],"detection":[5,135],"(SOD)":[6],"models":[7,44],"adopt":[8],"a":[9,46,62,72,115,158],"two-stream":[10],"structure":[11,67,80],"to":[12,70,86,148,155,167,188],"extract":[13,87],"the":[14,17,78,144,151,170,175,183,192,195,201,216,221],"information":[15,173,187],"from":[16],"input":[18],"RGB":[19,92],"and":[20,32,89,93,185,200,218,236],"depth":[21,94],"images.":[22],"Since":[23],"they":[24],"use":[25],"two":[26,83],"subnetworks":[27,85],"for":[28,38,131,150,206],"unimodal":[29,91,102],"feature":[30,35,65,161],"extraction":[31],"multiple":[33,104],"multi-modal":[34,125,160,179],"fusion":[36,66,118,162,176],"modules":[37],"extracting":[39],"cross-modal":[40,171,197,203],"complementary":[41,172],"information,":[42],"these":[43],"require":[45],"huge":[47],"number":[48],"of":[49,99,122,177,194,220],"parameters,":[50],"thus":[51],"hindering":[52],"their":[53],"real-life":[54],"applications.":[55],"To":[56],"remedy":[57],"this":[58],"situation,":[59],"we":[60,109,190],"propose":[61],"novel":[63],"middle-level":[64,90,101,178,198],"that":[68],"allows":[69],"design":[71],"lightweight":[73],"SOD":[75],"model.":[76],"Specifically,":[77],"proposed":[79,222,230],"first":[81],"employs":[82],"shallow":[84],"low-":[88],"features,":[95],"respectively.":[96],"Afterward,":[97],"instead":[98],"integrating":[100],"features":[103,127,199,205],"times":[105],"at":[106,238],"different":[107],"layers,":[108],"just":[110],"fuse":[111],"them":[112],"once":[113],"via":[114,136],"specially":[116,165],"designed":[117,166],"module.":[119],"On":[120],"top":[121],"that,":[123],"high-level":[124,204],"semantic":[126],"are":[128],"further":[129],"extracted":[130,202],"final":[132],"an":[137],"additional":[138],"subnetwork.":[139],"This":[140],"will":[141],"greatly":[142],"reduce":[143],"network's":[145],"parameters.":[146],"Moreover,":[147],"compensate":[149],"performance":[152],"loss":[153],"due":[154],"parameter":[156],"deduction,":[157],"relation-aware":[159],"module":[163],"is":[164],"effectively":[168],"capture":[169],"during":[174],"features.":[180],"By":[181],"enabling":[182],"feature-level":[184],"decision-level":[186],"interact,":[189],"maximize":[191],"usage":[193],"fused":[196],"saliency":[207],"prediction.":[208],"Experimental":[209],"results":[210],"on":[211],"several":[212],"benchmark":[213],"datasets":[214],"verify":[215],"effectiveness":[217],"superiority":[219],"method":[223],"over":[224],"some":[225],"state-of-the-art":[226],"methods.":[227],"Remarkably,":[228],"our":[229],"model":[231],"has":[232],"only":[233],"3.9M":[234],"parameters":[235],"runs":[237],"33":[239],"FPS.":[240]},"counts_by_year":[{"year":2026,"cited_by_count":5},{"year":2025,"cited_by_count":19},{"year":2024,"cited_by_count":15},{"year":2023,"cited_by_count":11}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}
