{"id":"https://openalex.org/W7139110583","doi":"https://doi.org/10.20965/jaciii.2026.p0388","title":"Vanilla-YOLO: A Lightweight Algorithm for Breast Cancer Detection","display_name":"Vanilla-YOLO: A Lightweight Algorithm for Breast Cancer Detection","publication_year":2026,"publication_date":"2026-03-19","ids":{"openalex":"https://openalex.org/W7139110583","doi":"https://doi.org/10.20965/jaciii.2026.p0388"},"language":"en","primary_location":{"id":"doi:10.20965/jaciii.2026.p0388","is_oa":true,"landing_page_url":"https://doi.org/10.20965/jaciii.2026.p0388","pdf_url":null,"source":{"id":"https://openalex.org/S4511983","display_name":"Journal of Advanced Computational Intelligence and Intelligent Informatics","issn_l":"1343-0130","issn":["1343-0130","1883-8014"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4324309662","host_organization_name":"Fuji Technology Press Ltd.","host_organization_lineage":["https://openalex.org/P4324309662"],"host_organization_lineage_names":["Fuji Technology Press Ltd."],"type":"journal"},"license":"cc-by-nd","license_id":"https://openalex.org/licenses/cc-by-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Advanced Computational Intelligence and Intelligent Informatics","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://doi.org/10.20965/jaciii.2026.p0388","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5130102714","display_name":"Shu-Hua Li","orcid":null},"institutions":[{"id":"https://openalex.org/I137967721","display_name":"Map\u00faa University","ror":"https://ror.org/040rd2b57","country_code":"PH","type":"facility","lineage":["https://openalex.org/I137967721"]}],"countries":["PH"],"is_corresponding":false,"raw_author_name":"Shu-Hua Li","raw_affiliation_strings":["School of Graduate Studies, Mapua University, 658 Muralla Street, Intramuros, Manila 1002, Philippines"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Graduate Studies, Mapua University, 658 Muralla Street, Intramuros, Manila 1002, Philippines","institution_ids":["https://openalex.org/I137967721"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5096549932","display_name":"Mary Jane C. Samonte","orcid":null},"institutions":[{"id":"https://openalex.org/I137967721","display_name":"Map\u00faa University","ror":"https://ror.org/040rd2b57","country_code":"PH","type":"facility","lineage":["https://openalex.org/I137967721"]}],"countries":["PH"],"is_corresponding":false,"raw_author_name":"Mary Jane C. Samonte","raw_affiliation_strings":["School of Graduate Studies, Mapua University, 658 Muralla Street, Intramuros, Manila 1002, Philippines"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Graduate Studies, Mapua University, 658 Muralla Street, Intramuros, Manila 1002, Philippines","institution_ids":["https://openalex.org/I137967721"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101235275","display_name":"Fenglong Yan","orcid":"https://orcid.org/0009-0002-3867-9875"},"institutions":[{"id":"https://openalex.org/I4210131997","display_name":"Dalian Neusoft University of Information","ror":"https://ror.org/0304ty515","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210131997"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Feng-Long Yan","raw_affiliation_strings":["School of Computer and Software, Dalian Neusoft University of Information, 8 Software Park Road, Dalian 116023, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer and Software, Dalian Neusoft University of Information, 8 Software Park Road, Dalian 116023, China","institution_ids":["https://openalex.org/I4210131997"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.2853993,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"30","issue":"2","first_page":"388","last_page":"396"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10862","display_name":"AI in cancer detection","score":0.7817000150680542,"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"}},"topics":[{"id":"https://openalex.org/T10862","display_name":"AI in cancer detection","score":0.7817000150680542,"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"}},{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.0722000002861023,"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/T12702","display_name":"Brain Tumor Detection and Classification","score":0.019600000232458115,"subfield":{"id":"https://openalex.org/subfields/2808","display_name":"Neurology"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5385000109672546},{"id":"https://openalex.org/keywords/redundancy","display_name":"Redundancy (engineering)","score":0.49950000643730164},{"id":"https://openalex.org/keywords/breast-cancer","display_name":"Breast cancer","score":0.4918000102043152},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4571000039577484},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.41280001401901245},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.396699994802475}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8481000065803528},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5385000109672546},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.515999972820282},{"id":"https://openalex.org/C152124472","wikidata":"https://www.wikidata.org/wiki/Q1204361","display_name":"Redundancy (engineering)","level":2,"score":0.49950000643730164},{"id":"https://openalex.org/C530470458","wikidata":"https://www.wikidata.org/wiki/Q128581","display_name":"Breast cancer","level":3,"score":0.4918000102043152},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4571000039577484},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4478999972343445},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.41280001401901245},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.396699994802475},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3691999912261963},{"id":"https://openalex.org/C165021410","wikidata":"https://www.wikidata.org/wiki/Q55564","display_name":"Lossy compression","level":2,"score":0.3580999970436096},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.3140999972820282},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.3073999881744385},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.2831999957561493},{"id":"https://openalex.org/C2780472235","wikidata":"https://www.wikidata.org/wiki/Q324634","display_name":"Mammography","level":4,"score":0.2685999870300293},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.26080000400543213}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.20965/jaciii.2026.p0388","is_oa":true,"landing_page_url":"https://doi.org/10.20965/jaciii.2026.p0388","pdf_url":null,"source":{"id":"https://openalex.org/S4511983","display_name":"Journal of Advanced Computational Intelligence and Intelligent Informatics","issn_l":"1343-0130","issn":["1343-0130","1883-8014"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4324309662","host_organization_name":"Fuji Technology Press Ltd.","host_organization_lineage":["https://openalex.org/P4324309662"],"host_organization_lineage_names":["Fuji Technology Press Ltd."],"type":"journal"},"license":"cc-by-nd","license_id":"https://openalex.org/licenses/cc-by-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Advanced Computational Intelligence and Intelligent Informatics","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.20965/jaciii.2026.p0388","is_oa":true,"landing_page_url":"https://doi.org/10.20965/jaciii.2026.p0388","pdf_url":null,"source":{"id":"https://openalex.org/S4511983","display_name":"Journal of Advanced Computational Intelligence and Intelligent Informatics","issn_l":"1343-0130","issn":["1343-0130","1883-8014"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4324309662","host_organization_name":"Fuji Technology Press Ltd.","host_organization_lineage":["https://openalex.org/P4324309662"],"host_organization_lineage_names":["Fuji Technology Press Ltd."],"type":"journal"},"license":"cc-by-nd","license_id":"https://openalex.org/licenses/cc-by-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Advanced Computational Intelligence and Intelligent Informatics","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Good health and well-being","score":0.638207197189331,"id":"https://metadata.un.org/sdg/3"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W2963037989","https://openalex.org/W3158337936","https://openalex.org/W4313357378","https://openalex.org/W4376613708","https://openalex.org/W4384305743","https://openalex.org/W4386076325","https://openalex.org/W4387799420","https://openalex.org/W4388823657","https://openalex.org/W4390008348","https://openalex.org/W4401685465","https://openalex.org/W4409292836","https://openalex.org/W4409494569","https://openalex.org/W7133243929"],"related_works":[],"abstract_inverted_index":{"As":[0],"a":[1,78,113,167,204],"receptor":[2,13],"of":[3,51,63,71,81,128,166,181,193],"breast":[4,20,52],"cancer":[5,21,26,53],"prognosis":[6],"and":[7,23,36,67,73,76,135,153,179,189,223],"treatment,":[8],"human":[9],"epidermal":[10],"growth":[11],"factor":[12],"2":[14],"(HER-2)":[15],"is":[16,90,101,142,197,203],"closely":[17],"associated":[18],"with":[19,40],"occurrence":[22],"progression.":[24],"Breast":[25],"lesions":[27,39,75],"are":[28],"characterized":[29],"by":[30,123],"irregular":[31],"shapes,":[32],"small":[33,72],"lesion":[34],"targets,":[35],"possible":[37],"multi-target":[38,74],"overlapping":[41],"boundaries.":[42],"Existing":[43],"algorithms":[44],"have":[45],"partly":[46],"improved":[47,99,195,201],"the":[48,61,125,129,139,145,159,164,177,194,200],"detection":[49,54,65,69,121,133,187],"accuracy":[50,66,122,188,192],"model.":[55],"However,":[56],"it":[57],"still":[58],"suffers":[59],"from":[60],"issues":[62],"insufficient":[64],"slow":[68],"speed":[70,134],"requires":[77],"huge":[79],"mass":[80],"sample":[82],"data":[83],"for":[84],"iteration":[85],"during":[86],"model":[87,100,110,130,196,202],"training,":[88],"which":[89,184],"demanding":[91],"on":[92,107],"datasets.":[93],"To":[94],"address":[95],"this":[96,104],"problem,":[97],"an":[98],"proposed":[102],"in":[103],"paper":[105],"based":[106],"YOLOv10.":[108],"The":[109,191],"introduces":[111],"VanillaNet,":[112],"lightweight":[114,168],"backbone":[115],"network":[116,126,162,217],"that":[117],"can":[118],"significantly":[119],"improve":[120],"reducing":[124],"depth":[127],"to":[131,148],"equalize":[132],"performance.":[136],"In":[137,158],"addition,":[138],"RefConv":[140],"module":[141,175],"embedded":[143],"into":[144],"C2f":[146],"structure":[147],"further":[149],"reduce":[150],"channel":[151],"redundancy":[152],"smooth":[154],"out":[155],"lossy":[156],"situations.":[157],"feature":[160,172],"fusion":[161],"part,":[163],"introduction":[165],"up-sampling":[169],"operator":[170],"content-aware":[171],"reorganization":[173],"CARAFE":[174],"enhances":[176],"quality":[178],"richness":[180],"output":[182],"features,":[183],"effectively":[185],"improves":[186],"speed.":[190],"98.8%.":[198],"Thus,":[199],"significant":[205],"advantage":[206],"over":[207],"mainstream":[208],"models":[209],"such":[210],"as":[211],"traditional":[212],"faster":[213],"region-based":[214],"convolutional":[215],"neural":[216],"(RCNN),":[218],"YOLOv5,":[219],"YOLOv7,":[220],"YOLOv8,":[221],"YOLOv10,":[222],"YOLOv12.":[224]},"counts_by_year":[],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2026-03-20T00:00:00"}
