{"id":"https://openalex.org/W3203626837","doi":"https://doi.org/10.1109/csaiee54046.2021.9543197","title":"Cartoon Figure Recognition with The Deep Residual Network","display_name":"Cartoon Figure Recognition with The Deep Residual Network","publication_year":2021,"publication_date":"2021-08-20","ids":{"openalex":"https://openalex.org/W3203626837","doi":"https://doi.org/10.1109/csaiee54046.2021.9543197","mag":"3203626837"},"language":"en","primary_location":{"id":"doi:10.1109/csaiee54046.2021.9543197","doi":"https://doi.org/10.1109/csaiee54046.2021.9543197","is_oa":false,"landing_page_url":"https://doi.org/10.1109/csaiee54046.2021.9543197","pdf_url":null,"source":{"id":"https://openalex.org/S7407105484","display_name":"IEEE International Conference on Computer Science, Artificial Intelligence and Electronic Engineering (CSAIEE)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Conference on Computer Science, Artificial Intelligence and Electronic Engineering (CSAIEE)","raw_type":"proceedings-article"},"volume":null,"type":"conference-paper","is_traditional":true,"indexed_in":["crossref"],"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/A5084559992","display_name":"Ziyi Guo","orcid":"https://orcid.org/0000-0002-0811-5086","observed_orcids":["https://orcid.org/0000-0002-0811-5086","https://orcid.org/0009-0009-8785-4052"]},"institutions":[{"id":"https://openalex.org/I184681353","display_name":"Anhui University of Science and Technology","ror":"https://ror.org/00q9atg80","country_code":"CN","type":"education","lineage":["https://openalex.org/I184681353"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Ziyi Guo","raw_affiliation_strings":["School of mechanical engineering, Anhui University of Science and Technology, AUST, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of mechanical engineering, Anhui University of Science and Technology, AUST, Beijing, China","institution_ids":["https://openalex.org/I184681353"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5084559992"],"corresponding_institution_ids":["https://openalex.org/I184681353"],"apc_list":null,"apc_paid":null,"fwci":0.3081,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.5924399,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":88,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"157","last_page":"160"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9965999722480774,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9965999722480774,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.0010999999940395355,"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/T13674","display_name":"Computer Science and Engineering","score":0.0005000000237487257,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/resnet","display_name":"ResNet","score":0.7179999947547913},{"id":"https://openalex.org/keywords/convolutional-neural-networks","display_name":"convolutional neural networks","score":0.7250000238418579},{"id":"https://openalex.org/keywords/lstm","display_name":"LSTM","score":0.7559999823570251},{"id":"https://openalex.org/keywords/image-rotation","display_name":"image rotation","score":0.4009999930858612},{"id":"https://openalex.org/keywords/data-augmentation","display_name":"data augmentation","score":0.7419999837875366},{"id":"https://openalex.org/keywords/image-preprocessing","display_name":"image preprocessing","score":0.6990000009536743},{"id":"https://openalex.org/keywords/network-structure-comparison","display_name":"network structure comparison","score":0.5699999928474426}],"concepts":[{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.7959319353103638},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7839221954345703},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7565591335296631},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.6392189264297485},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5896194577217102},{"id":"https://openalex.org/C13743948","wikidata":"https://www.wikidata.org/wiki/Q45842","display_name":"Web crawler","level":2,"score":0.522984504699707},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.5177423357963562},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5066033601760864},{"id":"https://openalex.org/C2780861071","wikidata":"https://www.wikidata.org/wiki/Q1062934","display_name":"Character (mathematics)","level":2,"score":0.4697563648223877},{"id":"https://openalex.org/C546480517","wikidata":"https://www.wikidata.org/wiki/Q167555","display_name":"Optical character recognition","level":3,"score":0.4512714743614197},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.42210283875465393},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.41700923442840576},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.13713058829307556},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.08122357726097107},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.0},{"id":"https://openalex.org/C78458016","wikidata":"https://www.wikidata.org/wiki/Q840400","display_name":"Evolutionary biology","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/csaiee54046.2021.9543197","doi":"https://doi.org/10.1109/csaiee54046.2021.9543197","is_oa":false,"landing_page_url":"https://doi.org/10.1109/csaiee54046.2021.9543197","pdf_url":null,"source":{"id":"https://openalex.org/S7407105484","display_name":"IEEE International Conference on Computer Science, Artificial Intelligence and Electronic Engineering (CSAIEE)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Conference on Computer Science, Artificial Intelligence and Electronic Engineering (CSAIEE)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":7,"referenced_works":["https://openalex.org/W1665214252","https://openalex.org/W2163605009","https://openalex.org/W2194775991","https://openalex.org/W2302255633","https://openalex.org/W2546302380","https://openalex.org/W2753713840","https://openalex.org/W2767072113"],"related_works":["https://openalex.org/W4386920444","https://openalex.org/W4210618991","https://openalex.org/W3156648560","https://openalex.org/W4414184276","https://openalex.org/W3092663764","https://openalex.org/W2988413199","https://openalex.org/W3216285697","https://openalex.org/W4285412153","https://openalex.org/W3209908437","https://openalex.org/W3134939346"],"abstract_inverted_index":{"Because":[0],"of":[1,5,27,31,54,74,77,118,128,135,143,191],"the":[2,25,32,62,75,81,93,98,103,112,116,120,126,129,133,147,150,166,173,188],"wide":[3],"application":[4],"deep":[6],"learning,":[7],"there":[8,20],"are":[9,21],"more":[10],"neural":[11,48,148],"network":[12,36,49,154,157,175],"structures":[13,50],"in":[14,24,35,72],"image":[15,28,55],"recognition":[16,29],"technology":[17],"nowadays,":[18],"but":[19],"various":[22,33],"differences":[23,34,63],"accuracy":[26,76,183],"because":[30],"structures.":[37],"For":[38],"this":[39],"reason,":[40],"it":[41],"is":[42],"especially":[43],"important":[44],"to":[45,96,124,164,185],"use":[46],"different":[47,52,86,137,141],"for":[51,140],"forms":[53,139,142],"data.":[56,105,168],"This":[57],"paper":[58],"focuses":[59],"on":[60,111],"exploring":[61],"between":[64],"LSTM":[65,151],"networks,":[66,68],"residual":[67,160,178],"and":[69,90,101,115,155],"CNN":[70,153,156,174],"networks":[71],"terms":[73],"cartoon":[78,87],"character":[79,88],"recognition.[1]Firstly,":[80],"web":[82],"crawler":[83],"acquires":[84],"14":[85],"images":[89,100,121],"manually":[91],"screens":[92],"original":[94],"data":[95,107,144],"remove":[97],"duplicate":[99],"obtain":[102],"preliminary":[104,113],"Then":[106],"enhancement":[108],"was":[109,122],"performed":[110],"data,":[114,130],"form":[117],"rotating":[119],"selected":[123],"complete":[125],"pre-processing":[127],"which":[131],"solved":[132],"problem":[134],"using":[136],"code":[138],"importing":[145],"into":[146],"network;":[149],"network,":[152],"with":[158,177,187],"added":[159],"function":[161,179],"were":[162],"used":[163],"recognize":[165],"pre-processed":[167],"The":[169],"experiments":[170],"show":[171],"that":[172],"structure":[176],"can":[180],"achieve":[181],"higher":[182],"compared":[184],"LSTM,":[186],"final":[189],"result":[190],"76.08%.":[192]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1}],"updated_date":"2026-10-27T15:51:10.671819","created_date":"2021-10-11T00:00:00"}
