{"id":"https://openalex.org/W3108916041","doi":"https://doi.org/10.1007/s00371-020-02024-y","title":"3D car shape reconstruction from a contour sketch using GAN and lazy learning","display_name":"3D car shape reconstruction from a contour sketch using GAN and lazy learning","publication_year":2021,"publication_date":"2021-04-16","ids":{"openalex":"https://openalex.org/W3108916041","doi":"https://doi.org/10.1007/s00371-020-02024-y","mag":"3108916041"},"language":"en","primary_location":{"id":"doi:10.1007/s00371-020-02024-y","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s00371-020-02024-y","pdf_url":"https://link.springer.com/content/pdf/10.1007/s00371-020-02024-y.pdf","source":{"id":"https://openalex.org/S73060445","display_name":"The Visual Computer","issn_l":"0178-2789","issn":["0178-2789","1432-2315"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"The Visual Computer","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://link.springer.com/content/pdf/10.1007/s00371-020-02024-y.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5087508199","display_name":"Naoki Nozawa","orcid":null},"institutions":[{"id":"https://openalex.org/I150744194","display_name":"Waseda University","ror":"https://ror.org/00ntfnx83","country_code":"JP","type":"education","lineage":["https://openalex.org/I150744194"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Naoki Nozawa","raw_affiliation_strings":["Department of Pure and Applied Physics, Waseda University, Tokyo, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Pure and Applied Physics, Waseda University, Tokyo, Japan","institution_ids":["https://openalex.org/I150744194"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5038258635","display_name":"Hubert P. H. Shum","orcid":"https://orcid.org/0000-0001-5651-6039"},"institutions":[{"id":"https://openalex.org/I190082696","display_name":"Durham University","ror":"https://ror.org/01v29qb04","country_code":"GB","type":"education","lineage":["https://openalex.org/I190082696"]},{"id":"https://openalex.org/I32394136","display_name":"Northumbria University","ror":"https://ror.org/049e6bc10","country_code":"GB","type":"education","lineage":["https://openalex.org/I32394136"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"Hubert P. H. Shum","raw_affiliation_strings":["Department of Computer Science, Durham University, Durham, UK","Department of Computer and Information Sciences, Northumbria University, Newcastle upon Tyne, UK"],"raw_orcid":"https://orcid.org/0000-0001-5651-6039","affiliations":[{"raw_affiliation_string":"Department of Computer Science, Durham University, Durham, UK","institution_ids":["https://openalex.org/I190082696"]},{"raw_affiliation_string":"Department of Computer and Information Sciences, Northumbria University, Newcastle upon Tyne, UK","institution_ids":["https://openalex.org/I32394136"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101959004","display_name":"Qi Feng","orcid":"https://orcid.org/0000-0002-6892-3122"},"institutions":[{"id":"https://openalex.org/I150744194","display_name":"Waseda University","ror":"https://ror.org/00ntfnx83","country_code":"JP","type":"education","lineage":["https://openalex.org/I150744194"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Qi Feng","raw_affiliation_strings":["Department of Pure and Applied Physics, Waseda University, Tokyo, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Pure and Applied Physics, Waseda University, Tokyo, Japan","institution_ids":["https://openalex.org/I150744194"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5080180158","display_name":"Edmond S. L. Ho","orcid":"https://orcid.org/0000-0001-5862-106X"},"institutions":[{"id":"https://openalex.org/I32394136","display_name":"Northumbria University","ror":"https://ror.org/049e6bc10","country_code":"GB","type":"education","lineage":["https://openalex.org/I32394136"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Edmond S. L. Ho","raw_affiliation_strings":["Department of Computer and Information Sciences, Northumbria University, Newcastle upon Tyne, UK"],"raw_orcid":"https://orcid.org/0000-0001-5862-106X","affiliations":[{"raw_affiliation_string":"Department of Computer and Information Sciences, Northumbria University, Newcastle upon Tyne, UK","institution_ids":["https://openalex.org/I32394136"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5083427215","display_name":"Shigeo Morishima","orcid":"https://orcid.org/0000-0001-8859-6539"},"institutions":[{"id":"https://openalex.org/I150744194","display_name":"Waseda University","ror":"https://ror.org/00ntfnx83","country_code":"JP","type":"education","lineage":["https://openalex.org/I150744194"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Shigeo Morishima","raw_affiliation_strings":["Waseda Research Institute for Science and Engineering, Waseda University, Tokyo, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Waseda Research Institute for Science and Engineering, Waseda University, Tokyo, Japan","institution_ids":["https://openalex.org/I150744194"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5038258635"],"corresponding_institution_ids":["https://openalex.org/I190082696","https://openalex.org/I32394136"],"apc_list":{"value":2990,"currency":"USD","value_usd":2990},"apc_paid":{"value":2990,"currency":"USD","value_usd":2990},"fwci":2.7353,"has_fulltext":true,"cited_by_count":22,"citation_normalized_percentile":{"value":0.90052783,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"38","issue":"4","first_page":"1317","last_page":"1330"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10719","display_name":"3D Shape Modeling and Analysis","score":0.9995999932289124,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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/T10719","display_name":"3D Shape Modeling and Analysis","score":0.9995999932289124,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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/T10531","display_name":"Advanced Vision and Imaging","score":0.9987999796867371,"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/T10481","display_name":"Computer Graphics and Visualization Techniques","score":0.9977999925613403,"subfield":{"id":"https://openalex.org/subfields/1704","display_name":"Computer Graphics and Computer-Aided Design"},"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/computer-science","display_name":"Computer science","score":0.8302656412124634},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7022050619125366},{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.6803553700447083},{"id":"https://openalex.org/keywords/sketch","display_name":"Sketch","score":0.6357488632202148},{"id":"https://openalex.org/keywords/pipeline","display_name":"Pipeline (software)","score":0.6152985095977783},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5276966094970703},{"id":"https://openalex.org/keywords/subspace-topology","display_name":"Subspace topology","score":0.523451030254364},{"id":"https://openalex.org/keywords/computer-graphics","display_name":"Computer graphics","score":0.5063058137893677},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.48026132583618164},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.46739113330841064},{"id":"https://openalex.org/keywords/graphics","display_name":"Graphics","score":0.44518348574638367},{"id":"https://openalex.org/keywords/generative-model","display_name":"Generative model","score":0.414128839969635},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.3768202066421509},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3319926857948303},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.33192962408065796},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.20298221707344055},{"id":"https://openalex.org/keywords/computer-graphics","display_name":"Computer graphics (images)","score":0.16376382112503052}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8302656412124634},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7022050619125366},{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.6803553700447083},{"id":"https://openalex.org/C2779231336","wikidata":"https://www.wikidata.org/wiki/Q7534724","display_name":"Sketch","level":2,"score":0.6357488632202148},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.6152985095977783},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5276966094970703},{"id":"https://openalex.org/C32834561","wikidata":"https://www.wikidata.org/wiki/Q660730","display_name":"Subspace topology","level":2,"score":0.523451030254364},{"id":"https://openalex.org/C77660652","wikidata":"https://www.wikidata.org/wiki/Q150971","display_name":"Computer graphics","level":2,"score":0.5063058137893677},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.48026132583618164},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.46739113330841064},{"id":"https://openalex.org/C21442007","wikidata":"https://www.wikidata.org/wiki/Q1027879","display_name":"Graphics","level":2,"score":0.44518348574638367},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.414128839969635},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.3768202066421509},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3319926857948303},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.33192962408065796},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.20298221707344055},{"id":"https://openalex.org/C121684516","wikidata":"https://www.wikidata.org/wiki/Q7600677","display_name":"Computer graphics (images)","level":1,"score":0.16376382112503052},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1007/s00371-020-02024-y","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s00371-020-02024-y","pdf_url":"https://link.springer.com/content/pdf/10.1007/s00371-020-02024-y.pdf","source":{"id":"https://openalex.org/S73060445","display_name":"The Visual Computer","issn_l":"0178-2789","issn":["0178-2789","1432-2315"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"The Visual Computer","raw_type":"journal-article"},{"id":"pmh:oai:dro.dur.ac.uk.OAI2:33535","is_oa":false,"landing_page_url":"http://dro.dur.ac.uk/33535/","pdf_url":null,"source":{"id":"https://openalex.org/S4306400188","display_name":"Durham Research Online (Durham University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I190082696","host_organization_name":"Durham University","host_organization_lineage":["https://openalex.org/I190082696"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":"The Visual Computer, 2022, Vol.38(4), pp.1317-1330 [Peer Reviewed Journal]","raw_type":"Article"},{"id":"pmh:oai:eprints.gla.ac.uk:276352","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4210235606","display_name":"ENLIGHTEN (Jurnal Bimbingan dan Konseling Islam)","issn_l":"2622-8912","issn":["2622-8912","2622-8920"],"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-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":"","raw_type":"Articles"}],"best_oa_location":{"id":"doi:10.1007/s00371-020-02024-y","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s00371-020-02024-y","pdf_url":"https://link.springer.com/content/pdf/10.1007/s00371-020-02024-y.pdf","source":{"id":"https://openalex.org/S73060445","display_name":"The Visual Computer","issn_l":"0178-2789","issn":["0178-2789","1432-2315"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"The Visual Computer","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Decent work and economic growth","id":"https://metadata.un.org/sdg/8","score":0.6600000262260437}],"awards":[{"id":"https://openalex.org/G2517514485","display_name":null,"funder_award_id":"IES R2 181024","funder_id":"https://openalex.org/F4320320006","funder_display_name":"Royal Society"},{"id":"https://openalex.org/G432938063","display_name":null,"funder_award_id":"JPMJAC1602","funder_id":"https://openalex.org/F4320338113","funder_display_name":"Accelerated Innovation Research Initiative Turning Top Science and Ideas into High-Impact Values"},{"id":"https://openalex.org/G5004185486","display_name":"Analysis of Reality Distorted Spatio-Temporal Field to Improve Human Skill and Motivation","funder_award_id":"19H01129","funder_id":"https://openalex.org/F4320334764","funder_display_name":"Japan Society for the Promotion of Science"},{"id":"https://openalex.org/G5205327250","display_name":null,"funder_award_id":"JP19H01129","funder_id":"https://openalex.org/F4320334764","funder_display_name":"Japan Society for the Promotion of Science"},{"id":"https://openalex.org/G531938765","display_name":null,"funder_award_id":"IES\\R1\\191147","funder_id":"https://openalex.org/F4320320006","funder_display_name":"Royal Society"},{"id":"https://openalex.org/G5585255138","display_name":null,"funder_award_id":"IES R1 191147","funder_id":"https://openalex.org/F4320320006","funder_display_name":"Royal Society"},{"id":"https://openalex.org/G592943454","display_name":null,"funder_award_id":"IES\\R2\\181024 and IES\\R1\\191147","funder_id":"https://openalex.org/F4320320006","funder_display_name":"Royal Society"},{"id":"https://openalex.org/G6597667118","display_name":null,"funder_award_id":"JPMJMI19B2","funder_id":"https://openalex.org/F4320338243","funder_display_name":"JST-Mirai Program"},{"id":"https://openalex.org/G8660529049","display_name":null,"funder_award_id":"IES\\R2\\181024","funder_id":"https://openalex.org/F4320320006","funder_display_name":"Royal Society"}],"funders":[{"id":"https://openalex.org/F4320320006","display_name":"Royal Society","ror":"https://ror.org/03wnrjx87"},{"id":"https://openalex.org/F4320334764","display_name":"Japan Society for the Promotion of Science","ror":"https://ror.org/00hhkn466"},{"id":"https://openalex.org/F4320338113","display_name":"Accelerated Innovation Research Initiative Turning Top Science and Ideas into High-Impact Values","ror":null},{"id":"https://openalex.org/F4320338243","display_name":"JST-Mirai Program","ror":null}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3108916041.pdf","grobid_xml":"https://content.openalex.org/works/W3108916041.grobid-xml"},"referenced_works_count":52,"referenced_works":["https://openalex.org/W10311529","https://openalex.org/W170527118","https://openalex.org/W1965902026","https://openalex.org/W1982905909","https://openalex.org/W2013033433","https://openalex.org/W2018350972","https://openalex.org/W2026687385","https://openalex.org/W2039586391","https://openalex.org/W2045677161","https://openalex.org/W2059642890","https://openalex.org/W2071634722","https://openalex.org/W2119693472","https://openalex.org/W2121927366","https://openalex.org/W2133280623","https://openalex.org/W2135060907","https://openalex.org/W2137808436","https://openalex.org/W2145023731","https://openalex.org/W2169611956","https://openalex.org/W2190691619","https://openalex.org/W2237250383","https://openalex.org/W2339754110","https://openalex.org/W2342277278","https://openalex.org/W2471222198","https://openalex.org/W2499182527","https://openalex.org/W2560609797","https://openalex.org/W2560722161","https://openalex.org/W2603429625","https://openalex.org/W2621941845","https://openalex.org/W2739245956","https://openalex.org/W2775428617","https://openalex.org/W2795508634","https://openalex.org/W2796174671","https://openalex.org/W2798336850","https://openalex.org/W2895596173","https://openalex.org/W2902627232","https://openalex.org/W2913266832","https://openalex.org/W2962780596","https://openalex.org/W2963073614","https://openalex.org/W2963121255","https://openalex.org/W2963420272","https://openalex.org/W2963522749","https://openalex.org/W2963600949","https://openalex.org/W2963636051","https://openalex.org/W2963800363","https://openalex.org/W2963876278","https://openalex.org/W3011393807","https://openalex.org/W3028314732","https://openalex.org/W3101027576","https://openalex.org/W4232678584","https://openalex.org/W4251279517","https://openalex.org/W4300629176","https://openalex.org/W6608993855"],"related_works":["https://openalex.org/W4365211920","https://openalex.org/W3014948380","https://openalex.org/W2470043383","https://openalex.org/W4380551139","https://openalex.org/W2953501176","https://openalex.org/W2965095304","https://openalex.org/W2280377497","https://openalex.org/W3034474024","https://openalex.org/W3174044702","https://openalex.org/W4238433571"],"abstract_inverted_index":{"Abstract":[0],"3D":[1,42,57],"car":[2,43,58],"models":[3,21,59],"are":[4],"heavily":[5],"used":[6],"in":[7,136,177],"computer":[8],"games,":[9],"visual":[10],"effects,":[11],"and":[12,60,66,97,167],"even":[13],"automotive":[14],"designs.":[15],"As":[16],"a":[17,36,41,45,53,83,92,102,118,129,152,192],"result,":[18],"producing":[19],"such":[20,205],"with":[22,72,155,183,191],"minimal":[23,73],"labour":[24],"costs":[25],"is":[26,82,106,126,140,171],"increasingly":[27],"more":[28],"important.":[29],"To":[30],"tackle":[31],"the":[32,80,89,114,133,137,162,207],"challenge,":[33],"we":[34],"propose":[35],"novel":[37],"system":[38,50,81],"to":[39,146,173],"reconstruct":[40],"using":[44,200],"single":[46,193],"sketch":[47],"image.":[48],"The":[49,77],"learns":[51],"from":[52],"synthetic":[54],"database":[55],"of":[56,79,91,108,117,121,165,181],"their":[61],"corresponding":[62],"2D":[63],"contour":[64],"sketches":[65],"segmentation":[67],"masks,":[68],"allowing":[69],"effective":[70,115],"training":[71],"data":[74,111,157],"collection":[75],"cost.":[76],"core":[78],"machine":[84,202],"learning":[85,104,143,169,203],"pipeline":[86],"that":[87,127,161],"combines":[88],"use":[90,164],"generative":[93],"adversarial":[94],"network":[95],"(GAN)":[96],"lazy":[98,168],"learning.":[99],"GAN,":[100],"being":[101],"deep":[103],"method,":[105,131],"capable":[107],"modelling":[109,116,132],"complicated":[110,184],"distributions,":[112],"enabling":[113],"large":[119],"variety":[120],"cars.":[122],"Its":[123],"major":[124],"weakness":[125],"as":[128,206],"global":[130],"fine":[134],"details":[135],"local":[138,148,153,185],"region":[139],"challenging.":[141],"Lazy":[142],"works":[144],"well":[145],"preserve":[147],"features":[149,186],"by":[150],"generating":[151],"subspace":[154],"relevant":[156],"samples.":[158],"We":[159],"demonstrate":[160],"combined":[163],"GAN":[166],"produces":[170],"able":[172],"produce":[174],"high-quality":[175],"results,":[176],"which":[178],"different":[179],"types":[180],"cars":[182],"can":[187],"be":[188],"generated":[189],"effectively":[190],"sketch.":[194],"Our":[195],"method":[196],"outperforms":[197],"existing":[198],"ones":[199],"other":[201],"structures":[204],"variational":[208],"autoencoder.":[209]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":6},{"year":2022,"cited_by_count":9},{"year":2021,"cited_by_count":1}],"updated_date":"2026-07-23T08:03:31.855105","created_date":"2025-10-10T00:00:00"}
