{"id":"https://openalex.org/W4318054412","doi":"https://doi.org/10.3390/rs15030708","title":"Gradual Domain Adaptation with Pseudo-Label Denoising for SAR Target Recognition When Using Only Synthetic Data for Training","display_name":"Gradual Domain Adaptation with Pseudo-Label Denoising for SAR Target Recognition When Using Only Synthetic Data for Training","publication_year":2023,"publication_date":"2023-01-25","ids":{"openalex":"https://openalex.org/W4318054412","doi":"https://doi.org/10.3390/rs15030708"},"language":"en","primary_location":{"id":"doi:10.3390/rs15030708","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs15030708","pdf_url":"https://www.mdpi.com/2072-4292/15/3/708/pdf?version=1675756101","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/2072-4292/15/3/708/pdf?version=1675756101","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5035629666","display_name":"Yuanshuang Sun","orcid":"https://orcid.org/0000-0002-9735-0415"},"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":"Yuanshuang Sun","raw_affiliation_strings":["National Laboratory of Radar Signal Processing, Xidian University, Xi\u2019an 710071, China","National Laboratory of Radar Signal Processing, Xidian University, Xi'an 710071, China"],"affiliations":[{"raw_affiliation_string":"National Laboratory of Radar Signal Processing, Xidian University, Xi\u2019an 710071, China","institution_ids":["https://openalex.org/I149594827"]},{"raw_affiliation_string":"National Laboratory of Radar Signal Processing, Xidian University, Xi'an 710071, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5018469371","display_name":"Yinghua Wang","orcid":null},"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":"Yinghua Wang","raw_affiliation_strings":["National Laboratory of Radar Signal Processing, Xidian University, Xi\u2019an 710071, China","National Laboratory of Radar Signal Processing, Xidian University, Xi'an 710071, China"],"affiliations":[{"raw_affiliation_string":"National Laboratory of Radar Signal Processing, Xidian University, Xi\u2019an 710071, China","institution_ids":["https://openalex.org/I149594827"]},{"raw_affiliation_string":"National Laboratory of Radar Signal Processing, Xidian University, Xi'an 710071, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100411968","display_name":"Hongwei Liu","orcid":"https://orcid.org/0000-0003-4046-163X"},"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":"Hongwei Liu","raw_affiliation_strings":["National Laboratory of Radar Signal Processing, Xidian University, Xi\u2019an 710071, China","National Laboratory of Radar Signal Processing, Xidian University, Xi'an 710071, China"],"affiliations":[{"raw_affiliation_string":"National Laboratory of Radar Signal Processing, Xidian University, Xi\u2019an 710071, China","institution_ids":["https://openalex.org/I149594827"]},{"raw_affiliation_string":"National Laboratory of Radar Signal Processing, Xidian University, Xi'an 710071, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5007314199","display_name":"Liping Hu","orcid":"https://orcid.org/0000-0002-3241-5070"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liping Hu","raw_affiliation_strings":["Science and Technology on Electromagnetic Scattering Laboratory, Beijing Institute of Environmental Features, Beijing 100854, China"],"affiliations":[{"raw_affiliation_string":"Science and Technology on Electromagnetic Scattering Laboratory, Beijing Institute of Environmental Features, Beijing 100854, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5026884594","display_name":"Chen Zhang","orcid":"https://orcid.org/0000-0002-0486-8208"},"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":"Chen Zhang","raw_affiliation_strings":["National Laboratory of Radar Signal Processing, Xidian University, Xi\u2019an 710071, China","National Laboratory of Radar Signal Processing, Xidian University, Xi'an 710071, China"],"affiliations":[{"raw_affiliation_string":"National Laboratory of Radar Signal Processing, Xidian University, Xi\u2019an 710071, China","institution_ids":["https://openalex.org/I149594827"]},{"raw_affiliation_string":"National Laboratory of Radar Signal Processing, Xidian University, Xi'an 710071, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100440540","display_name":"Siyuan Wang","orcid":"https://orcid.org/0000-0001-7174-9754"},"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":"Siyuan Wang","raw_affiliation_strings":["National Laboratory of Radar Signal Processing, Xidian University, Xi\u2019an 710071, China","National Laboratory of Radar Signal Processing, Xidian University, Xi'an 710071, China"],"affiliations":[{"raw_affiliation_string":"National Laboratory of Radar Signal Processing, Xidian University, Xi\u2019an 710071, China","institution_ids":["https://openalex.org/I149594827"]},{"raw_affiliation_string":"National Laboratory of Radar Signal Processing, Xidian University, Xi'an 710071, China","institution_ids":["https://openalex.org/I149594827"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5018469371"],"corresponding_institution_ids":["https://openalex.org/I149594827"],"apc_list":{"value":2500,"currency":"CHF","value_usd":2707},"apc_paid":{"value":2500,"currency":"CHF","value_usd":2707},"fwci":18.9409,"has_fulltext":false,"cited_by_count":23,"citation_normalized_percentile":{"value":0.98919591,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"15","issue":"3","first_page":"708","last_page":"708"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11038","display_name":"Advanced SAR Imaging Techniques","score":0.9993000030517578,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11038","display_name":"Advanced SAR Imaging Techniques","score":0.9993000030517578,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"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":0.9916999936103821,"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/T10801","display_name":"Synthetic Aperture Radar (SAR) Applications and Techniques","score":0.9889000058174133,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8122575879096985},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6836581230163574},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6686816215515137},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.5383601784706116},{"id":"https://openalex.org/keywords/test-data","display_name":"Test data","score":0.5344117879867554},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5141165852546692},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.478023886680603},{"id":"https://openalex.org/keywords/synthetic-data","display_name":"Synthetic data","score":0.46889442205429077},{"id":"https://openalex.org/keywords/synthetic-aperture-radar","display_name":"Synthetic aperture radar","score":0.4491189122200012},{"id":"https://openalex.org/keywords/automatic-target-recognition","display_name":"Automatic target recognition","score":0.44432270526885986},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4438899755477905},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.42944738268852234},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.32947224378585815}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8122575879096985},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6836581230163574},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6686816215515137},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.5383601784706116},{"id":"https://openalex.org/C16910744","wikidata":"https://www.wikidata.org/wiki/Q7705759","display_name":"Test data","level":2,"score":0.5344117879867554},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5141165852546692},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.478023886680603},{"id":"https://openalex.org/C160920958","wikidata":"https://www.wikidata.org/wiki/Q7662746","display_name":"Synthetic data","level":2,"score":0.46889442205429077},{"id":"https://openalex.org/C87360688","wikidata":"https://www.wikidata.org/wiki/Q740686","display_name":"Synthetic aperture radar","level":2,"score":0.4491189122200012},{"id":"https://openalex.org/C117623542","wikidata":"https://www.wikidata.org/wiki/Q621974","display_name":"Automatic target recognition","level":3,"score":0.44432270526885986},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4438899755477905},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.42944738268852234},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.32947224378585815},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"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":3,"locations":[{"id":"doi:10.3390/rs15030708","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs15030708","pdf_url":"https://www.mdpi.com/2072-4292/15/3/708/pdf?version=1675756101","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:8cbe7274039e4c0fb4d51866a9f579bd","is_oa":true,"landing_page_url":"https://doaj.org/article/8cbe7274039e4c0fb4d51866a9f579bd","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Remote Sensing, Vol 15, Iss 3, p 708 (2023)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/2072-4292/15/3/708/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/rs15030708","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"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":"Remote Sensing; Volume 15; Issue 3; Pages: 708","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/rs15030708","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs15030708","pdf_url":"https://www.mdpi.com/2072-4292/15/3/708/pdf?version=1675756101","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2466457629","display_name":null,"funder_award_id":"KGJ202206","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3476442746","display_name":null,"funder_award_id":"61671354","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"}],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4318054412.pdf"},"referenced_works_count":68,"referenced_works":["https://openalex.org/W1571809481","https://openalex.org/W1731081199","https://openalex.org/W1966040997","https://openalex.org/W1994197834","https://openalex.org/W2095705004","https://openalex.org/W2152498377","https://openalex.org/W2159291411","https://openalex.org/W2165698076","https://openalex.org/W2187089797","https://openalex.org/W2292481059","https://openalex.org/W2410591237","https://openalex.org/W2594718649","https://openalex.org/W2615263668","https://openalex.org/W2730249686","https://openalex.org/W2752788177","https://openalex.org/W2759213214","https://openalex.org/W2774061875","https://openalex.org/W2786808285","https://openalex.org/W2793888044","https://openalex.org/W2887280559","https://openalex.org/W2890897299","https://openalex.org/W2901459322","https://openalex.org/W2931068004","https://openalex.org/W2945014618","https://openalex.org/W2945137370","https://openalex.org/W2945637781","https://openalex.org/W2963870446","https://openalex.org/W2964288524","https://openalex.org/W2965619422","https://openalex.org/W2971884209","https://openalex.org/W2981395580","https://openalex.org/W2998624838","https://openalex.org/W3010159779","https://openalex.org/W3023371261","https://openalex.org/W3035050044","https://openalex.org/W3039883906","https://openalex.org/W3056736931","https://openalex.org/W3128476715","https://openalex.org/W3130456161","https://openalex.org/W3130848852","https://openalex.org/W3131740536","https://openalex.org/W3152264159","https://openalex.org/W3155803391","https://openalex.org/W3159063287","https://openalex.org/W3171229070","https://openalex.org/W3205091368","https://openalex.org/W3207009651","https://openalex.org/W3207649199","https://openalex.org/W3207752736","https://openalex.org/W3213042253","https://openalex.org/W4206588109","https://openalex.org/W4210260455","https://openalex.org/W4211083893","https://openalex.org/W4226146307","https://openalex.org/W4285129541","https://openalex.org/W4312761526","https://openalex.org/W4319586835","https://openalex.org/W6634226609","https://openalex.org/W6637618735","https://openalex.org/W6674330103","https://openalex.org/W6696636527","https://openalex.org/W6748312029","https://openalex.org/W6791050018","https://openalex.org/W6793809909","https://openalex.org/W6802087428","https://openalex.org/W6802893204","https://openalex.org/W6806838726","https://openalex.org/W6839628212"],"related_works":["https://openalex.org/W4225274307","https://openalex.org/W4283015542","https://openalex.org/W4380446748","https://openalex.org/W2074425837","https://openalex.org/W4312659495","https://openalex.org/W2945014618","https://openalex.org/W3101007570","https://openalex.org/W4387910575","https://openalex.org/W2002992601","https://openalex.org/W209733029"],"abstract_inverted_index":{"Because":[0],"of":[1,5,17,214,232,246],"the":[2,15,29,45,58,78,87,101,114,117,121,131,137,142,160,170,175,179,189,202,209,212,227,230,244],"high":[3],"cost":[4],"data":[6,21,37,53,109,123,126],"acquisition":[7],"in":[8],"synthetic":[9,18,36,49],"aperture":[10],"radar":[11],"(SAR)":[12],"target":[13],"recognition,":[14],"application":[16],"(simulated)":[19],"SAR":[20,52],"is":[22,83],"becoming":[23],"increasingly":[24],"popular.":[25],"Our":[26],"study":[27],"explores":[28],"problems":[30],"encountered":[31],"when":[32],"training":[33,122,198],"fully":[34],"on":[35,40,169,188],"and":[38,44,50,91,124,136,158,181,194,218,236],"testing":[39],"measured":[41,51],"(real)":[42],"data,":[43],"distribution":[46,118],"gap":[47],"between":[48,120,178],"affects":[54],"recognition":[55,66,96,253],"performance":[56,144],"under":[57],"circumstances.":[59],"We":[60,164,184],"propose":[61],"a":[62,76,93],"gradual":[63],"domain":[64],"adaptation":[65],"framework":[67,210,228],"with":[68,255],"pseudo-label":[69,151,166],"denoising":[70,152,167],"to":[71,85,112,153,173,200],"solve":[72],"this":[73],"problem.":[74],"As":[75],"warm-up,":[77],"feature":[79,89,182],"alignment":[80],"classification":[81],"network":[82],"trained":[84,161],"learn":[86],"domain-invariant":[88],"representation":[90],"obtain":[92],"relatively":[94],"satisfactory":[95],"result.":[97],"Then,":[98],"we":[99,149,195],"utilize":[100],"self-training":[102],"method":[103],"for":[104,127],"further":[105],"improvement.":[106],"Some":[107],"pseudo-labeled":[108],"are":[110,133],"selected":[111],"fine-tune":[113],"network,":[115],"narrowing":[116],"difference":[119],"test":[125],"each":[128],"category.":[129],"However,":[130],"pseudo-labels":[132,157],"inevitably":[134],"noisy,":[135],"wrong":[138],"ones":[139],"may":[140],"deteriorate":[141],"classifier\u2019s":[143,162],"during":[145],"fine-tuning":[146],"iterations.":[147],"Thus,":[148],"conduct":[150,185],"eliminate":[154],"some":[155],"noisy":[156],"improve":[159],"robustness.":[163],"perform":[165],"based":[168],"image":[171,180],"similarity":[172],"keep":[174],"label":[176],"consistent":[177],"domains.":[183],"extensive":[186],"experiments":[187],"newly":[190],"published":[191],"SAMPLE":[192],"dataset,":[193],"design":[196],"two":[197],"scenarios":[199],"verify":[201],"proposed":[203],"framework.":[204],"For":[205,223],"Training":[206,224],"Scenario":[207,225],"I,":[208],"matches":[211],"result":[213],"neural":[215],"architecture":[216],"searching":[217],"achieves":[219,237],"96.46%":[220],"average":[221,239],"accuracy.":[222,240],"II,":[226],"outperforms":[229],"results":[231,242],"other":[233],"existing":[234],"methods":[235],"97.36%":[238],"These":[241],"illustrate":[243],"superiority":[245],"our":[247],"framework,":[248],"which":[249],"can":[250],"reach":[251],"state-of-the-art":[252],"levels":[254],"appropriate":[256],"stability.":[257]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":10},{"year":2024,"cited_by_count":10},{"year":2023,"cited_by_count":2}],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2023-01-26T00:00:00"}