{"id":"https://openalex.org/W2955931003","doi":"https://doi.org/10.1186/s40537-019-0222-3","title":"Feature visualization in comic artist classification using deep neural networks","display_name":"Feature visualization in comic artist classification using deep neural networks","publication_year":2019,"publication_date":"2019-06-25","ids":{"openalex":"https://openalex.org/W2955931003","doi":"https://doi.org/10.1186/s40537-019-0222-3","mag":"2955931003"},"language":"en","primary_location":{"id":"doi:10.1186/s40537-019-0222-3","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s40537-019-0222-3","pdf_url":"https://journalofbigdata.springeropen.com/track/pdf/10.1186/s40537-019-0222-3.pdf","source":{"id":"https://openalex.org/S2737955091","display_name":"Journal Of Big Data","issn_l":"2196-1115","issn":["2196-1115"],"is_oa":true,"is_in_doaj":true,"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":"Journal of Big Data","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://journalofbigdata.springeropen.com/track/pdf/10.1186/s40537-019-0222-3.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100337302","display_name":"Young-Min Kim","orcid":"https://orcid.org/0000-0002-6914-901X"},"institutions":[{"id":"https://openalex.org/I4575257","display_name":"Hanyang University","ror":"https://ror.org/046865y68","country_code":"KR","type":"education","lineage":["https://openalex.org/I4575257"]},{"id":"https://openalex.org/I93906172","display_name":"Anyang University","ror":"https://ror.org/018pdh902","country_code":"KR","type":"education","lineage":["https://openalex.org/I93906172"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Kim Young-Min","raw_affiliation_strings":["Graduate School of Technology & Innovation Management, Hanyang University, Wangsimni-ro, Seoul, South Korea"],"affiliations":[{"raw_affiliation_string":"Graduate School of Technology & Innovation Management, Hanyang University, Wangsimni-ro, Seoul, South Korea","institution_ids":["https://openalex.org/I93906172","https://openalex.org/I4575257"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5100337302"],"corresponding_institution_ids":["https://openalex.org/I4575257","https://openalex.org/I93906172"],"apc_list":{"value":1060,"currency":"GBP","value_usd":1300},"apc_paid":{"value":1060,"currency":"GBP","value_usd":1300},"fwci":0.8682,"has_fulltext":true,"cited_by_count":18,"citation_normalized_percentile":{"value":0.72207637,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"6","issue":"1","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12650","display_name":"Aesthetic Perception and Analysis","score":0.9873999953269958,"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"}},"topics":[{"id":"https://openalex.org/T12650","display_name":"Aesthetic Perception and Analysis","score":0.9873999953269958,"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"}},{"id":"https://openalex.org/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.9850000143051147,"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/T10758","display_name":"Cinema and Media Studies","score":0.9613000154495239,"subfield":{"id":"https://openalex.org/subfields/2002","display_name":"Economics and Econometrics"},"field":{"id":"https://openalex.org/fields/20","display_name":"Economics, Econometrics and Finance"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/comics","display_name":"Comics","score":0.8885362148284912},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.812140166759491},{"id":"https://openalex.org/keywords/visualization","display_name":"Visualization","score":0.7472805976867676},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.714878261089325},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6992626190185547},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.6750338673591614},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.590112030506134},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5500770807266235},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.5423373579978943},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5306165218353271},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.48457157611846924},{"id":"https://openalex.org/keywords/scope","display_name":"Scope (computer science)","score":0.4844341576099396},{"id":"https://openalex.org/keywords/visual-analytics","display_name":"Visual analytics","score":0.4511158764362335},{"id":"https://openalex.org/keywords/deep-neural-networks","display_name":"Deep neural networks","score":0.4198300838470459},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.4163951873779297},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3346688747406006},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.21294498443603516}],"concepts":[{"id":"https://openalex.org/C529099274","wikidata":"https://www.wikidata.org/wiki/Q1004","display_name":"Comics","level":2,"score":0.8885362148284912},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.812140166759491},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.7472805976867676},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.714878261089325},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6992626190185547},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.6750338673591614},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.590112030506134},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5500770807266235},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.5423373579978943},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5306165218353271},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.48457157611846924},{"id":"https://openalex.org/C2778012447","wikidata":"https://www.wikidata.org/wiki/Q1034415","display_name":"Scope (computer science)","level":2,"score":0.4844341576099396},{"id":"https://openalex.org/C59732488","wikidata":"https://www.wikidata.org/wiki/Q2528440","display_name":"Visual analytics","level":3,"score":0.4511158764362335},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.4198300838470459},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.4163951873779297},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3346688747406006},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.21294498443603516},{"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/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1186/s40537-019-0222-3","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s40537-019-0222-3","pdf_url":"https://journalofbigdata.springeropen.com/track/pdf/10.1186/s40537-019-0222-3.pdf","source":{"id":"https://openalex.org/S2737955091","display_name":"Journal Of Big Data","issn_l":"2196-1115","issn":["2196-1115"],"is_oa":true,"is_in_doaj":true,"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":"Journal of Big Data","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:cb9dca08df1e477b91f973f9be6645ae","is_oa":true,"landing_page_url":"https://doaj.org/article/cb9dca08df1e477b91f973f9be6645ae","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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Journal of Big Data, Vol 6, Iss 1, Pp 1-18 (2019)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1186/s40537-019-0222-3","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s40537-019-0222-3","pdf_url":"https://journalofbigdata.springeropen.com/track/pdf/10.1186/s40537-019-0222-3.pdf","source":{"id":"https://openalex.org/S2737955091","display_name":"Journal Of Big Data","issn_l":"2196-1115","issn":["2196-1115"],"is_oa":true,"is_in_doaj":true,"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":"Journal of Big Data","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G5092055710","display_name":null,"funder_award_id":"000000","funder_id":"https://openalex.org/F4320321681","funder_display_name":"Ministry of Trade, Industry and Energy"},{"id":"https://openalex.org/G6580423611","display_name":null,"funder_award_id":"201600000002255","funder_id":"https://openalex.org/F4320321142","funder_display_name":"Hanyang University"}],"funders":[{"id":"https://openalex.org/F4320321142","display_name":"Hanyang University","ror":"https://ror.org/046865y68"},{"id":"https://openalex.org/F4320321681","display_name":"Ministry of Trade, Industry and Energy","ror":"https://ror.org/008nkqk13"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2955931003.pdf","grobid_xml":"https://content.openalex.org/works/W2955931003.grobid-xml"},"referenced_works_count":38,"referenced_works":["https://openalex.org/W296507979","https://openalex.org/W1622449098","https://openalex.org/W1825675169","https://openalex.org/W1934410531","https://openalex.org/W1995258346","https://openalex.org/W1998969073","https://openalex.org/W2097117768","https://openalex.org/W2102605133","https://openalex.org/W2108240927","https://openalex.org/W2166242527","https://openalex.org/W2190008860","https://openalex.org/W2192954843","https://openalex.org/W2194775991","https://openalex.org/W2475287302","https://openalex.org/W2510733224","https://openalex.org/W2604737827","https://openalex.org/W2607041014","https://openalex.org/W2608703264","https://openalex.org/W2618530766","https://openalex.org/W2619098877","https://openalex.org/W2747543643","https://openalex.org/W2753498304","https://openalex.org/W2785972335","https://openalex.org/W2794640211","https://openalex.org/W2798729263","https://openalex.org/W2809757976","https://openalex.org/W2962835968","https://openalex.org/W2962837952","https://openalex.org/W2962880358","https://openalex.org/W2962883796","https://openalex.org/W2963278124","https://openalex.org/W2963336115","https://openalex.org/W2963460133","https://openalex.org/W2963729050","https://openalex.org/W2963989815","https://openalex.org/W2964101377","https://openalex.org/W3101659800","https://openalex.org/W4229494842"],"related_works":["https://openalex.org/W3201315974","https://openalex.org/W3015688758","https://openalex.org/W3216780987","https://openalex.org/W3171682447","https://openalex.org/W610194060","https://openalex.org/W608774069","https://openalex.org/W2921140335","https://openalex.org/W2005234362","https://openalex.org/W2162970382","https://openalex.org/W1997235926"],"abstract_inverted_index":{"Deep":[0],"neural":[1,59,74,169],"networks":[2],"have":[3,24,43],"become":[4],"a":[5,72,88,96],"standard":[6],"framework":[7],"for":[8,54,65,102],"image":[9],"analytics.":[10],"Besides":[11],"the":[12,21,28,31,92,103,113,118,131,148,153],"traditional":[13],"applications,":[14],"such":[15,40],"as":[16,41],"object":[17,141],"classification":[18,56,67,166],"and":[19,71],"detection,":[20],"latest":[22],"studies":[23],"started":[25],"to":[26,33,78,112,116,151],"expand":[27],"scope":[29],"of":[30,100,139,147,156,163],"applications":[32],"include":[34],"artworks.":[35],"However,":[36],"popular":[37],"art":[38],"forms,":[39],"comics,":[42],"been":[44],"ignored":[45],"in":[46,124,161],"this":[47],"trend.":[48],"This":[49,143],"study":[50],"investigates":[51],"visual":[52,120,154],"features":[53,133],"comic":[55,66,80,164],"using":[57,158],"deep":[58,168],"networks.":[60,170],"An":[61],"effective":[62],"input":[63],"format":[64],"is":[68,76,109],"first":[69,149],"defined,":[70],"convolutional":[73],"network":[75],"used":[77],"classify":[79],"images":[81],"into":[82],"eight":[83],"different":[84,136],"artist":[85],"categories.":[86],"Using":[87],"publicly":[89],"available":[90],"dataset,":[91],"trained":[93,114],"model":[94],"obtains":[95],"mean":[97],"F1":[98],"score":[99],"84%":[101],"classification.":[104,125,142],"A":[105],"feature":[106,159],"visualization":[107],"technique":[108],"also":[110],"applied":[111],"classifier,":[115],"verify":[117],"internal":[119],"characteristics":[121,155],"that":[122,130],"succeed":[123],"The":[126],"experimental":[127],"result":[128],"shows":[129],"visualized":[132],"are":[134],"significantly":[135],"from":[137],"those":[138],"general":[140],"work":[144],"represents":[145],"one":[146],"attempts":[150],"examine":[152],"comics":[157],"visualization,":[160],"terms":[162],"author":[165],"with":[167]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":6},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":2}],"updated_date":"2026-04-10T15:06:20.359241","created_date":"2025-10-10T00:00:00"}
