{"id":"https://openalex.org/W2105473101","doi":"https://doi.org/10.1109/tip.2010.2079551","title":"Adaptive Multiwavelet-Based Watermarking Through JPW Masking","display_name":"Adaptive Multiwavelet-Based Watermarking Through JPW Masking","publication_year":2010,"publication_date":"2010-09-29","ids":{"openalex":"https://openalex.org/W2105473101","doi":"https://doi.org/10.1109/tip.2010.2079551","mag":"2105473101","pmid":"https://pubmed.ncbi.nlm.nih.gov/20876023"},"language":"en","primary_location":{"id":"doi:10.1109/tip.2010.2079551","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2010.2079551","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":"https://openalex.org/A5066577872","display_name":"Lihong Cui","orcid":"https://orcid.org/0000-0002-0675-4095"},"institutions":[{"id":"https://openalex.org/I75390827","display_name":"Beijing University of Chemical Technology","ror":"https://ror.org/00df5yc52","country_code":"CN","type":"education","lineage":["https://openalex.org/I75390827"]},{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Lihong Cui","raw_affiliation_strings":["Department of Mathematics and Computer Science, Beijing University of Chemical Technology, Beijing 100080, China. mathcui@163.com","Dept. of Math. & Comput. Sci., Beijing Univ. of Chem. Technol., Beijing, China"],"affiliations":[{"raw_affiliation_string":"Department of Mathematics and Computer Science, Beijing University of Chemical Technology, Beijing 100080, China. mathcui@163.com","institution_ids":["https://openalex.org/I75390827"]},{"raw_affiliation_string":"Dept. of Math. & Comput. Sci., Beijing Univ. of Chem. Technol., Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101703146","display_name":"Wenguo Li","orcid":"https://orcid.org/0000-0001-7609-5884"},"institutions":[{"id":"https://openalex.org/I75390827","display_name":"Beijing University of Chemical Technology","ror":"https://ror.org/00df5yc52","country_code":"CN","type":"education","lineage":["https://openalex.org/I75390827"]},{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenguo Li","raw_affiliation_strings":["Department of Mathematics and Computer Science, Beijing University of Chemical and Technology, Beijing, China","Dept. of Math. & Comput. Sci., Beijing Univ. of Chem. Technol., Beijing, China"],"affiliations":[{"raw_affiliation_string":"Department of Mathematics and Computer Science, Beijing University of Chemical and Technology, Beijing, China","institution_ids":["https://openalex.org/I75390827"]},{"raw_affiliation_string":"Dept. of Math. & Comput. Sci., Beijing Univ. of Chem. Technol., Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5066577872"],"corresponding_institution_ids":["https://openalex.org/I20231570","https://openalex.org/I75390827"],"apc_list":null,"apc_paid":null,"fwci":5.4181,"has_fulltext":false,"cited_by_count":47,"citation_normalized_percentile":{"value":0.96317227,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"20","issue":"4","first_page":"1047","last_page":"1060"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10388","display_name":"Advanced Steganography and Watermarking Techniques","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/T10388","display_name":"Advanced Steganography and Watermarking Techniques","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/T10688","display_name":"Image and Signal Denoising Methods","score":0.9984999895095825,"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/T10901","display_name":"Advanced Data Compression Techniques","score":0.9973999857902527,"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/digital-watermarking","display_name":"Digital watermarking","score":0.8290557861328125},{"id":"https://openalex.org/keywords/watermark","display_name":"Watermark","score":0.7433509230613708},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.5802242755889893},{"id":"https://openalex.org/keywords/luminance","display_name":"Luminance","score":0.5574531555175781},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.538017213344574},{"id":"https://openalex.org/keywords/weighting","display_name":"Weighting","score":0.48814114928245544},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.47848910093307495},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.46988940238952637},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.45016464591026306},{"id":"https://openalex.org/keywords/distortion","display_name":"Distortion (music)","score":0.4402354061603546},{"id":"https://openalex.org/keywords/additive-white-gaussian-noise","display_name":"Additive white Gaussian noise","score":0.43300390243530273},{"id":"https://openalex.org/keywords/decoding-methods","display_name":"Decoding methods","score":0.4325541853904724},{"id":"https://openalex.org/keywords/generalized-normal-distribution","display_name":"Generalized normal distribution","score":0.4268518388271332},{"id":"https://openalex.org/keywords/gaussian-noise","display_name":"Gaussian noise","score":0.41765278577804565},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4092194437980652},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.37602484226226807},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.28381454944610596},{"id":"https://openalex.org/keywords/white-noise","display_name":"White noise","score":0.24101439118385315},{"id":"https://openalex.org/keywords/bandwidth","display_name":"Bandwidth (computing)","score":0.15783914923667908},{"id":"https://openalex.org/keywords/normal-distribution","display_name":"Normal distribution","score":0.11586642265319824},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.08760040998458862}],"concepts":[{"id":"https://openalex.org/C150817343","wikidata":"https://www.wikidata.org/wiki/Q875932","display_name":"Digital watermarking","level":3,"score":0.8290557861328125},{"id":"https://openalex.org/C164112704","wikidata":"https://www.wikidata.org/wiki/Q7974348","display_name":"Watermark","level":3,"score":0.7433509230613708},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.5802242755889893},{"id":"https://openalex.org/C73313986","wikidata":"https://www.wikidata.org/wiki/Q355386","display_name":"Luminance","level":2,"score":0.5574531555175781},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.538017213344574},{"id":"https://openalex.org/C183115368","wikidata":"https://www.wikidata.org/wiki/Q856577","display_name":"Weighting","level":2,"score":0.48814114928245544},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.47848910093307495},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.46988940238952637},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.45016464591026306},{"id":"https://openalex.org/C126780896","wikidata":"https://www.wikidata.org/wiki/Q899871","display_name":"Distortion (music)","level":4,"score":0.4402354061603546},{"id":"https://openalex.org/C169334058","wikidata":"https://www.wikidata.org/wiki/Q353292","display_name":"Additive white Gaussian noise","level":3,"score":0.43300390243530273},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.4325541853904724},{"id":"https://openalex.org/C171383496","wikidata":"https://www.wikidata.org/wiki/Q2497477","display_name":"Generalized normal distribution","level":3,"score":0.4268518388271332},{"id":"https://openalex.org/C4199805","wikidata":"https://www.wikidata.org/wiki/Q2725903","display_name":"Gaussian noise","level":2,"score":0.41765278577804565},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4092194437980652},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.37602484226226807},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.28381454944610596},{"id":"https://openalex.org/C112633086","wikidata":"https://www.wikidata.org/wiki/Q381287","display_name":"White noise","level":2,"score":0.24101439118385315},{"id":"https://openalex.org/C2776257435","wikidata":"https://www.wikidata.org/wiki/Q1576430","display_name":"Bandwidth (computing)","level":2,"score":0.15783914923667908},{"id":"https://openalex.org/C102094743","wikidata":"https://www.wikidata.org/wiki/Q133871","display_name":"Normal distribution","level":2,"score":0.11586642265319824},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.08760040998458862},{"id":"https://openalex.org/C194257627","wikidata":"https://www.wikidata.org/wiki/Q211554","display_name":"Amplifier","level":3,"score":0.0},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.0},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","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/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0}],"mesh":[{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D003196","descriptor_name":"Computer Graphics","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D003196","descriptor_name":"Computer Graphics","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D003196","descriptor_name":"Computer Graphics","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D007090","descriptor_name":"Image Interpretation, Computer-Assisted","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D007090","descriptor_name":"Image Interpretation, Computer-Assisted","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D007090","descriptor_name":"Image Interpretation, Computer-Assisted","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D010363","descriptor_name":"Pattern Recognition, Automated","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D010363","descriptor_name":"Pattern Recognition, Automated","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D010363","descriptor_name":"Pattern Recognition, Automated","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D011356","descriptor_name":"Product Labeling","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D011356","descriptor_name":"Product Labeling","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D011356","descriptor_name":"Product Labeling","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D012680","descriptor_name":"Sensitivity and Specificity","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D012680","descriptor_name":"Sensitivity and Specificity","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D012680","descriptor_name":"Sensitivity and Specificity","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D015203","descriptor_name":"Reproducibility of Results","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D015203","descriptor_name":"Reproducibility of Results","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D015203","descriptor_name":"Reproducibility of Results","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D044962","descriptor_name":"Data Compression","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D044962","descriptor_name":"Data Compression","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D044962","descriptor_name":"Data Compression","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D058067","descriptor_name":"Wavelet Analysis","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D058067","descriptor_name":"Wavelet Analysis","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D058067","descriptor_name":"Wavelet Analysis","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true}],"locations_count":2,"locations":[{"id":"doi:10.1109/tip.2010.2079551","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2010.2079551","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:20876023","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/20876023","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":[],"funders":[{"id":"https://openalex.org/F4320321913","display_name":"Beijing University of Technology","ror":"https://ror.org/037b1pp87"},{"id":"https://openalex.org/F4320324303","display_name":"Beijing University of Chemical Technology","ror":"https://ror.org/00df5yc52"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":50,"referenced_works":["https://openalex.org/W51203759","https://openalex.org/W1528207269","https://openalex.org/W1987406538","https://openalex.org/W1993744827","https://openalex.org/W2046463768","https://openalex.org/W2048247182","https://openalex.org/W2049348043","https://openalex.org/W2062024414","https://openalex.org/W2064347257","https://openalex.org/W2076482367","https://openalex.org/W2084112876","https://openalex.org/W2086805717","https://openalex.org/W2089646143","https://openalex.org/W2092368531","https://openalex.org/W2096178037","https://openalex.org/W2098408114","https://openalex.org/W2104170824","https://openalex.org/W2109411320","https://openalex.org/W2116124511","https://openalex.org/W2116467012","https://openalex.org/W2120400964","https://openalex.org/W2123865683","https://openalex.org/W2125620133","https://openalex.org/W2126323701","https://openalex.org/W2126660587","https://openalex.org/W2132984323","https://openalex.org/W2133924821","https://openalex.org/W2135537163","https://openalex.org/W2137866167","https://openalex.org/W2141858002","https://openalex.org/W2143085920","https://openalex.org/W2143601630","https://openalex.org/W2145792107","https://openalex.org/W2147444658","https://openalex.org/W2148593155","https://openalex.org/W2154710242","https://openalex.org/W2156848867","https://openalex.org/W2158821445","https://openalex.org/W2160515090","https://openalex.org/W2163534628","https://openalex.org/W2164364763","https://openalex.org/W2164678342","https://openalex.org/W2164978881","https://openalex.org/W2168078737","https://openalex.org/W2169035906","https://openalex.org/W2169111714","https://openalex.org/W2169488613","https://openalex.org/W2171730653","https://openalex.org/W4255272544","https://openalex.org/W6679805591"],"related_works":["https://openalex.org/W2593105627","https://openalex.org/W1911817635","https://openalex.org/W2810224748","https://openalex.org/W2353656796","https://openalex.org/W2011915004","https://openalex.org/W2074565401","https://openalex.org/W1967187784","https://openalex.org/W2242778450","https://openalex.org/W2380803194","https://openalex.org/W2186922242"],"abstract_inverted_index":{"In":[0,73],"this":[1],"paper,":[2],"a":[3,33,118,172],"multibit,":[4],"multiplicative,":[5],"spread":[6],"spectrum":[7],"watermarking":[8,95,140],"using":[9,117],"the":[10,55,70,107,130,133,146,156,159,167],"discrete":[11],"multiwavelet":[12,127,136],"(including":[13],"unbalanced":[14],"and":[15,66,162],"balanced":[16],"multiwavelet)":[17],"transform":[18],"is":[19,28,89,97,115,142],"presented.":[20],"Performance":[21],"improvement":[22],"with":[23,171],"respect":[24],"to":[25,58,75,86,100],"existing":[26],"algorithm":[27],"obtained":[29],"by":[30,51,105],"means":[31],"of":[32,47,68,129,135,158,166,174],"new":[34,41],"just":[35],"perceptual":[36,83,103],"weighting":[37,85],"(JPW)":[38],"model.":[39,109],"The":[40],"model":[42,120,153],"incorporates":[43],"various":[44],"masking":[45],"effects":[46],"human":[48],"visual":[49],"perception":[50],"taking":[52],"into":[53],"account":[54],"eye's":[56],"sensitivity":[57,84],"noise":[59,87],"changes":[60],"depending":[61],"on":[62,122,138],"spatial":[63],"frequency,":[64],"luminance":[65],"texture":[67],"all":[69],"image":[71,161],"subbands.":[72],"contrast":[74],"conventional":[76],"JND":[77],"threshold":[78],"model,":[79],"JPW":[80,108,152],"describing":[81],"minimum":[82,102],"changes,":[88],"fitter":[90],"for":[91,126],"nonadditive":[92],"watermarking.":[93],"Specifically,":[94],"strength":[96],"adaptively":[98],"adjusted":[99],"obtain":[101],"distortion":[104],"employing":[106],"Correspondingly,":[110],"an":[111],"adaptive":[112],"optimum":[113],"decoding":[114],"derived":[116],"statistic":[119],"based":[121],"generalized-Gaussian":[123],"distribution":[124],"(GGD)":[125],"coefficients":[128],"cover-image.":[131],"Furthermore,":[132],"impact":[134],"characteristics":[137],"proposed":[139,151],"scheme":[141],"also":[143],"analyzed.":[144],"Finally,":[145],"experimental":[147],"results":[148],"show":[149],"that":[150],"can":[154],"improve":[155],"quality":[157],"watermarked":[160],"give":[163],"more":[164],"robustness":[165],"watermark":[168],"as":[169],"compared":[170],"variety":[173],"state-of-the-art":[175],"algorithms.":[176]},"counts_by_year":[{"year":2024,"cited_by_count":2},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":1},{"year":2018,"cited_by_count":4},{"year":2017,"cited_by_count":3},{"year":2016,"cited_by_count":3},{"year":2015,"cited_by_count":5},{"year":2014,"cited_by_count":6},{"year":2013,"cited_by_count":10},{"year":2012,"cited_by_count":5}],"updated_date":"2026-01-13T01:12:25.745995","created_date":"2025-10-10T00:00:00"}