{"id":"https://openalex.org/W4414184276","doi":"https://doi.org/10.32604/cmc.2025.067840","title":"Robust Multi-Label Cartoon Character Classification on the Novel Kral Sakir Dataset Using Deep Learning Techniques","display_name":"Robust Multi-Label Cartoon Character Classification on the Novel Kral Sakir Dataset Using Deep Learning Techniques","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4414184276","doi":"https://doi.org/10.32604/cmc.2025.067840"},"language":"en","primary_location":{"id":"doi:10.32604/cmc.2025.067840","is_oa":true,"landing_page_url":"https://doi.org/10.32604/cmc.2025.067840","pdf_url":null,"source":{"id":"https://openalex.org/S4210191605","display_name":"Computers, materials & continua/Computers, materials & continua (Print)","issn_l":"1546-2218","issn":["1546-2218","1546-2226"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computers, Materials & Continua","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://doi.org/10.32604/cmc.2025.067840","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5063373783","display_name":"Candan T\u00dcMER","orcid":"https://orcid.org/0000-0002-9592-7110"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Candan Tumer","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5012881590","display_name":"Erdal G\u00fcveno\u011flu","orcid":"https://orcid.org/0000-0003-1333-5953"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Erdal Guvenoglu","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5018339805","display_name":"Volkan Tunal\u0131","orcid":"https://orcid.org/0000-0002-2735-7996"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Volkan Tunali","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5063373783"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.37269283,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"85","issue":"3","first_page":"5135","last_page":"5158"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13373","display_name":"Data Mining and Machine Learning Applications","score":0.9697999954223633,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T13373","display_name":"Data Mining and Machine Learning Applications","score":0.9697999954223633,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T13538","display_name":"Linguistics and Language Analysis","score":0.9539999961853027,"subfield":{"id":"https://openalex.org/subfields/1203","display_name":"Language and Linguistics"},"field":{"id":"https://openalex.org/fields/12","display_name":"Arts and Humanities"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T14216","display_name":"Multimedia Learning Systems","score":0.9452999830245972,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/benchmark","display_name":"Benchmark (surveying)","score":0.76910001039505},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.71670001745224},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6976000070571899},{"id":"https://openalex.org/keywords/character","display_name":"Character (mathematics)","score":0.608299970626831},{"id":"https://openalex.org/keywords/transfer-of-learning","display_name":"Transfer of learning","score":0.5978999733924866},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5583000183105469},{"id":"https://openalex.org/keywords/baseline","display_name":"Baseline (sea)","score":0.48510000109672546},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.4544999897480011},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4153999984264374}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8271999955177307},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7759000062942505},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.76910001039505},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.71670001745224},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6976000070571899},{"id":"https://openalex.org/C2780861071","wikidata":"https://www.wikidata.org/wiki/Q1062934","display_name":"Character (mathematics)","level":2,"score":0.608299970626831},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.5978999733924866},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5583000183105469},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5076000094413757},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.48510000109672546},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.4544999897480011},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4153999984264374},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.3763999938964844},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.37549999356269836},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.34630000591278076},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.33869999647140503},{"id":"https://openalex.org/C2777737414","wikidata":"https://www.wikidata.org/wiki/Q4868296","display_name":"Font","level":2,"score":0.32690000534057617},{"id":"https://openalex.org/C206345919","wikidata":"https://www.wikidata.org/wiki/Q20380951","display_name":"Resource (disambiguation)","level":2,"score":0.3102000057697296},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.30090001225471497},{"id":"https://openalex.org/C546480517","wikidata":"https://www.wikidata.org/wiki/Q167555","display_name":"Optical character recognition","level":3,"score":0.2971999943256378},{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.2797999978065491},{"id":"https://openalex.org/C148524875","wikidata":"https://www.wikidata.org/wiki/Q6975395","display_name":"F1 score","level":2,"score":0.27079999446868896},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.2524000108242035},{"id":"https://openalex.org/C512654426","wikidata":"https://www.wikidata.org/wiki/Q19652","display_name":"Public domain","level":2,"score":0.25209999084472656},{"id":"https://openalex.org/C58471807","wikidata":"https://www.wikidata.org/wiki/Q327120","display_name":"Receiver operating characteristic","level":2,"score":0.2515999972820282}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.32604/cmc.2025.067840","is_oa":true,"landing_page_url":"https://doi.org/10.32604/cmc.2025.067840","pdf_url":null,"source":{"id":"https://openalex.org/S4210191605","display_name":"Computers, materials & continua/Computers, materials & continua (Print)","issn_l":"1546-2218","issn":["1546-2218","1546-2226"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computers, Materials & Continua","raw_type":"journal-article"},{"id":"pmh:oai:pure.atira.dk:openaire/3724a064-e39c-4238-a341-ca8c3dfea413","is_oa":true,"landing_page_url":"https://research-portal.uws.ac.uk/en/publications/3724a064-e39c-4238-a341-ca8c3dfea413","pdf_url":null,"source":{"id":"https://openalex.org/S4306402572","display_name":"The UWS Academic Portal (University of the West of Scotland)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I868834043","host_organization_name":"University of the West of Scotland","host_organization_lineage":["https://openalex.org/I868834043"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"T\u00fcmer, C, Guvenoglu, E & Tunali, V 2025, 'Robust multi-label cartoon character classification on the novel Kral Sakir dataset using deep learning techniques', Computers, Materials & Continua, vol. 85, no. 3, pp. 5135-5158. https://doi.org/10.32604/cmc.2025.067840","raw_type":"info:eu-repo/semantics/publishedVersion"}],"best_oa_location":{"id":"doi:10.32604/cmc.2025.067840","is_oa":true,"landing_page_url":"https://doi.org/10.32604/cmc.2025.067840","pdf_url":null,"source":{"id":"https://openalex.org/S4210191605","display_name":"Computers, materials & continua/Computers, materials & continua (Print)","issn_l":"1546-2218","issn":["1546-2218","1546-2226"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computers, Materials & Continua","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Automated":[0],"cartoon":[1,60],"character":[2,61,176],"recognition":[3,177],"is":[4,117],"crucial":[5],"for":[6,55,152,168],"applications":[7],"in":[8,21],"content":[9],"indexing,":[10],"filtering,":[11],"and":[12,87,105,131,155,174],"copyright":[13],"protection,":[14],"yet":[15],"it":[16],"faces":[17],"a":[18,47,70,90,118,157,165],"significant":[19],"challenge":[20],"animated":[22],"media":[23],"due":[24],"to":[25],"high":[26],"intra-class":[27],"visual":[28],"variability,":[29],"where":[30],"characters":[31],"frequently":[32],"alter":[33],"their":[34],"appearance.":[35],"To":[36],"address":[37],"this":[38,153],"problem,":[39],"we":[40],"introduce":[41],"the":[42,56,75,108,147],"novel":[43],"Kral":[44],"Sakir":[45],"dataset,":[46],"public":[48],"benchmark":[49,72],"of":[50,58,77,102,129,134,142,149],"16,725":[51],"images":[52],"specifically":[53],"curated":[54],"task":[57],"multi-label":[59],"classification":[62],"under":[63],"these":[64],"varied":[65],"conditions.":[66],"This":[67],"paper":[68],"conducts":[69],"comprehensive":[71],"study,":[73],"evaluating":[74],"performance":[76,159],"state-of-the-art":[78],"pretrained":[79,115],"Convolutional":[80],"Neural":[81],"Networks":[82],"(CNNs),":[83],"including":[84],"DenseNet,":[85],"ResNet,":[86],"VGG,":[88],"against":[89],"custom":[91],"baseline":[92,139],"model":[93],"trained":[94],"from":[95],"scratch.":[96],"Our":[97],"experiments,":[98],"evaluated":[99],"using":[100],"metrics":[101],"F1-Score,":[103],"accuracy,":[104],"Area":[106],"Under":[107],"ROC":[109],"Curve":[110],"(AUC),":[111],"demonstrate":[112],"that":[113],"fine-tuning":[114],"models":[116],"highly":[119],"effective":[120],"strategy.":[121],"The":[122,144,161],"best-performing":[123],"model,":[124],"DenseNet121,":[125],"achieved":[126],"an":[127,132],"F1-Score":[128],"0.9890":[130],"accuracy":[133],"0.9898,":[135],"significantly":[136],"outperforming":[137],"our":[138],"CNN":[140],"(F1-Score":[141],"0.9545).":[143],"findings":[145],"validate":[146],"power":[148],"transfer":[150],"learning":[151],"domain":[154],"establish":[156],"strong":[158],"benchmark.":[160],"introduced":[162],"dataset":[163],"provides":[164],"valuable":[166],"resource":[167],"future":[169],"research":[170],"into":[171],"developing":[172],"robust":[173],"accurate":[175],"systems.":[178]},"counts_by_year":[],"updated_date":"2026-03-07T16:01:11.037858","created_date":"2025-10-10T00:00:00"}