{"id":"https://openalex.org/W4381276436","doi":"https://doi.org/10.1109/access.2023.3275173","title":"Data Augmentation Based on Generative Adversarial Networks for Endoscopic Image Classification","display_name":"Data Augmentation Based on Generative Adversarial Networks for Endoscopic Image Classification","publication_year":2023,"publication_date":"2023-01-01","ids":{"openalex":"https://openalex.org/W4381276436","doi":"https://doi.org/10.1109/access.2023.3275173"},"language":"en","primary_location":{"id":"doi:10.1109/access.2023.3275173","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2023.3275173","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/10005208/10122914.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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 Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/6287639/10005208/10122914.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101581917","display_name":"Hyun-Cheol Park","orcid":"https://orcid.org/0000-0001-8280-4026"},"institutions":[{"id":"https://openalex.org/I4210158432","display_name":"National Institute for Mathematical Sciences","ror":"https://ror.org/04n7py080","country_code":"KR","type":"education","lineage":["https://openalex.org/I4210158432"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Hyun-Cheol Park","raw_affiliation_strings":["Division of Industrial Mathematics, National Institute for Mathematical Sciences, Daejeon, Republic of Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Division of Industrial Mathematics, National Institute for Mathematical Sciences, Daejeon, Republic of Korea","institution_ids":["https://openalex.org/I4210158432"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5064240395","display_name":"In-Pyo Hong","orcid":null},"institutions":[{"id":"https://openalex.org/I12832649","display_name":"Gachon University","ror":"https://ror.org/03ryywt80","country_code":"KR","type":"education","lineage":["https://openalex.org/I12832649"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"In-Pyo Hong","raw_affiliation_strings":["Department of Computer Engineering, Gachon University, Gyeonggi-do, Seongnam-si, Republic of Korea"],"raw_orcid":"https://orcid.org/0000-0003-1679-1268","affiliations":[{"raw_affiliation_string":"Department of Computer Engineering, Gachon University, Gyeonggi-do, Seongnam-si, Republic of Korea","institution_ids":["https://openalex.org/I12832649"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5050009251","display_name":"Sahadev Poudel","orcid":"https://orcid.org/0000-0002-6574-038X"},"institutions":[{"id":"https://openalex.org/I12832649","display_name":"Gachon University","ror":"https://ror.org/03ryywt80","country_code":"KR","type":"education","lineage":["https://openalex.org/I12832649"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Sahadev Poudel","raw_affiliation_strings":["Department of IT Convergence Engineering, Gachon University, Gyeonggi-do, Seongnam-si, Republic of Korea"],"raw_orcid":"https://orcid.org/0000-0002-6574-038X","affiliations":[{"raw_affiliation_string":"Department of IT Convergence Engineering, Gachon University, Gyeonggi-do, Seongnam-si, Republic of Korea","institution_ids":["https://openalex.org/I12832649"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101410165","display_name":"Chang Choi","orcid":"https://orcid.org/0000-0002-2276-2378"},"institutions":[{"id":"https://openalex.org/I12832649","display_name":"Gachon University","ror":"https://ror.org/03ryywt80","country_code":"KR","type":"education","lineage":["https://openalex.org/I12832649"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Chang Choi","raw_affiliation_strings":["Department of Computer Engineering, Gachon University, Gyeonggi-do, Seongnam-si, Republic of Korea"],"raw_orcid":"https://orcid.org/0000-0002-2276-2378","affiliations":[{"raw_affiliation_string":"Department of Computer Engineering, Gachon University, Gyeonggi-do, Seongnam-si, Republic of Korea","institution_ids":["https://openalex.org/I12832649"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5101581917"],"corresponding_institution_ids":["https://openalex.org/I4210158432"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":5.0842,"has_fulltext":true,"cited_by_count":23,"citation_normalized_percentile":{"value":0.95856136,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":"11","issue":null,"first_page":"49216","last_page":"49225"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10552","display_name":"Colorectal Cancer Screening and Detection","score":0.9894000291824341,"subfield":{"id":"https://openalex.org/subfields/2730","display_name":"Oncology"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},"topics":[{"id":"https://openalex.org/T10552","display_name":"Colorectal Cancer Screening and Detection","score":0.9894000291824341,"subfield":{"id":"https://openalex.org/subfields/2730","display_name":"Oncology"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T10688","display_name":"Image and Signal Denoising Methods","score":0.9690999984741211,"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/T11019","display_name":"Image Enhancement Techniques","score":0.9498999714851379,"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/adversarial-system","display_name":"Adversarial system","score":0.8049997091293335},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.753330409526825},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6535623073577881},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.5462283492088318},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.5322254300117493},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.5205332040786743},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5076092481613159},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4155796766281128},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.37439411878585815}],"concepts":[{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.8049997091293335},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.753330409526825},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6535623073577881},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.5462283492088318},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.5322254300117493},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.5205332040786743},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5076092481613159},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4155796766281128},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.37439411878585815}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2023.3275173","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2023.3275173","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/10005208/10122914.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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 Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:03f1422accaa412c9743db487ace929b","is_oa":true,"landing_page_url":"https://doaj.org/article/03f1422accaa412c9743db487ace929b","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 11, Pp 49216-49225 (2023)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2023.3275173","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2023.3275173","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/10005208/10122914.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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 Access","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.8600000143051147,"id":"https://metadata.un.org/sdg/3","display_name":"Good health and well-being"}],"awards":[{"id":"https://openalex.org/G2632280777","display_name":null,"funder_award_id":"2021R1A2B5B02087169","funder_id":"https://openalex.org/F4320322120","funder_display_name":"National Research Foundation of Korea"},{"id":"https://openalex.org/G5631530259","display_name":null,"funder_award_id":"GCU-202300780001","funder_id":"https://openalex.org/F4320321366","funder_display_name":"Gachon University"},{"id":"https://openalex.org/G921252724","display_name":null,"funder_award_id":"2021R1A2B5B02087169","funder_id":"https://openalex.org/F4320328359","funder_display_name":"Ministry of Science and ICT, South Korea"}],"funders":[{"id":"https://openalex.org/F4320320671","display_name":"National Research Foundation","ror":"https://ror.org/05s0g1g46"},{"id":"https://openalex.org/F4320321366","display_name":"Gachon University","ror":"https://ror.org/03ryywt80"},{"id":"https://openalex.org/F4320322120","display_name":"National Research Foundation of Korea","ror":"https://ror.org/013aysd81"},{"id":"https://openalex.org/F4320328359","display_name":"Ministry of Science and ICT, South Korea","ror":"https://ror.org/01wpjm123"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4381276436.pdf","grobid_xml":"https://content.openalex.org/works/W4381276436.grobid-xml"},"referenced_works_count":44,"referenced_works":["https://openalex.org/W1686810756","https://openalex.org/W2108598243","https://openalex.org/W2112796928","https://openalex.org/W2163605009","https://openalex.org/W2194775991","https://openalex.org/W2600174524","https://openalex.org/W2623808523","https://openalex.org/W2757894858","https://openalex.org/W2770173563","https://openalex.org/W2771691017","https://openalex.org/W2886553471","https://openalex.org/W2889871190","https://openalex.org/W2890139949","https://openalex.org/W2892269335","https://openalex.org/W2895067176","https://openalex.org/W2925126079","https://openalex.org/W2955425717","https://openalex.org/W2962770929","https://openalex.org/W2963446712","https://openalex.org/W2963767194","https://openalex.org/W2972256375","https://openalex.org/W2998557912","https://openalex.org/W3009789042","https://openalex.org/W3011210166","https://openalex.org/W3015714375","https://openalex.org/W3023402713","https://openalex.org/W3027866141","https://openalex.org/W3028272487","https://openalex.org/W3034720584","https://openalex.org/W3035574324","https://openalex.org/W3047625747","https://openalex.org/W3092462694","https://openalex.org/W3093045698","https://openalex.org/W3161781507","https://openalex.org/W3170841864","https://openalex.org/W3211983116","https://openalex.org/W6637373629","https://openalex.org/W6684191040","https://openalex.org/W6746638498","https://openalex.org/W6746910627","https://openalex.org/W6754923448","https://openalex.org/W6762718338","https://openalex.org/W6779093361","https://openalex.org/W6784094891"],"related_works":["https://openalex.org/W2502115930","https://openalex.org/W2482350142","https://openalex.org/W4246396837","https://openalex.org/W3126451824","https://openalex.org/W1561927205","https://openalex.org/W3191453585","https://openalex.org/W4297672492","https://openalex.org/W4310988119","https://openalex.org/W4285226279","https://openalex.org/W4288019534"],"abstract_inverted_index":{"The":[0],"incidence":[1],"of":[2,49,78,86,92,96,108,126,181,191],"cancer":[3],"among":[4],"modern":[5],"people":[6],"has":[7],"recently":[8,118],"increased":[9],"due":[10],"to":[11,58,82,117,122,187],"various":[12],"reasons":[13],"such":[14,71],"as":[15,41,72],"eating":[16],"habits,":[17],"smoking,":[18],"and":[19,60,153],"drinking.":[20],"Therefore,":[21,75],"medical":[22,63,87,127],"image":[23],"analysis":[24],"for":[25,46,150],"effective":[26],"disease":[27,94,102,198],"diagnosis":[28],"is":[29,39,55,130],"considered":[30],"an":[31],"extremely":[32],"important":[33],"diagnostic":[34],"tool.":[35],"In":[36],"particular,":[37],"endoscopy":[38],"used":[40,186],"a":[42,106,167,197],"representative":[43],"screening":[44],"method":[45],"diagnosing":[47],"diseases":[48],"the":[50,76,84,90,97,124,151,158,173,182,189,192],"digestive":[51,98],"system.":[52,99],"However,":[53],"it":[54],"quite":[56],"difficult":[57],"quickly":[59],"thoroughly":[61],"analyze":[62],"data":[64,135,149,163],"by":[65],"relying":[66],"solely":[67],"on":[68,166,203],"human":[69],"vision,":[70],"with":[73],"endoscopy.":[74],"purpose":[77],"this":[79],"study":[80],"was":[81,169,185],"reduce":[83],"fatigue":[85],"staff":[88],"through":[89],"use":[91],"automated":[93],"classification":[95,199],"To":[100],"automate":[101],"classification,":[103],"we":[104,133,195],"trained":[105],"total":[107],"six":[109],"models,":[110],"ranging":[111],"from":[112],"relatively":[113],"old":[114],"deep-learning-based":[115],"models":[116],"published":[119],"approaches.":[120],"Additionally,":[121],"increase":[123],"number":[125],"data,":[128],"which":[129,184],"generally":[131],"insufficient,":[132],"applied":[134,170],"augmentation":[136,164],"using":[137],"two":[138],"adversarial":[139],"generative":[140],"neural":[141],"network-based":[142],"models.":[143],"We":[144],"utilized":[145],"Kvasir":[146],"version":[147],"2":[148],"experiment":[152],"demonstrated":[154],"that":[155],"InceptionNet-V3":[156],"showed":[157],"best":[159],"performance":[160,178],"improvement":[161],"when":[162],"based":[165],"Star-GAN":[168],"experimentally.":[171],"Furthermore,":[172],"approach":[174],"also":[175],"exhibited":[176],"good":[177],"in":[179],"terms":[180],"F1-Score,":[183],"evaluate":[188],"safety":[190],"model.":[193],"Thus,":[194],"propose":[196],"automation":[200],"model":[201],"centered":[202],"safer":[204],"performance.":[205]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":10},{"year":2024,"cited_by_count":12}],"updated_date":"2026-05-06T08:25:59.206177","created_date":"2025-10-10T00:00:00"}
