{"id":"https://openalex.org/W7138936647","doi":"https://doi.org/10.1109/globecom59602.2025.11432087","title":"ViT-MAE-COA: Vision Transformer-Masked Autoencoder with Cheetah Optimization for Otitis Media Classification","display_name":"ViT-MAE-COA: Vision Transformer-Masked Autoencoder with Cheetah Optimization for Otitis Media Classification","publication_year":2025,"publication_date":"2025-12-08","ids":{"openalex":"https://openalex.org/W7138936647","doi":"https://doi.org/10.1109/globecom59602.2025.11432087"},"language":null,"primary_location":{"id":"doi:10.1109/globecom59602.2025.11432087","is_oa":false,"landing_page_url":"https://doi.org/10.1109/globecom59602.2025.11432087","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"GLOBECOM 2025 - 2025 IEEE Global Communications Conference","raw_type":"proceedings-article"},"type":"article","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/A5129984931","display_name":"Chandu Thota","orcid":null},"institutions":[{"id":"https://openalex.org/I17389662","display_name":"University of Nicosia","ror":"https://ror.org/04v18t651","country_code":"CY","type":"education","lineage":["https://openalex.org/I17389662"]}],"countries":["CY"],"is_corresponding":true,"raw_author_name":"Chandu Thota","raw_affiliation_strings":["University of Nicosia,Department of Computer Science Mobile Systems Laboratory (MoSys Lab),Nicosia,Cyprus"],"affiliations":[{"raw_affiliation_string":"University of Nicosia,Department of Computer Science Mobile Systems Laboratory (MoSys Lab),Nicosia,Cyprus","institution_ids":["https://openalex.org/I17389662"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5050729772","display_name":"Constandinos X. Mavromoustakis","orcid":"https://orcid.org/0000-0003-0333-8034"},"institutions":[{"id":"https://openalex.org/I17389662","display_name":"University of Nicosia","ror":"https://ror.org/04v18t651","country_code":"CY","type":"education","lineage":["https://openalex.org/I17389662"]}],"countries":["CY"],"is_corresponding":false,"raw_author_name":"Constandinos X. Mavromoustakis","raw_affiliation_strings":["University of Nicosia,Department of Computer Science Mobile Systems Laboratory (MoSys Lab),Nicosia,Cyprus"],"affiliations":[{"raw_affiliation_string":"University of Nicosia,Department of Computer Science Mobile Systems Laboratory (MoSys Lab),Nicosia,Cyprus","institution_ids":["https://openalex.org/I17389662"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5124215249","display_name":"Jordi Mongay Batalla","orcid":null},"institutions":[{"id":"https://openalex.org/I108403487","display_name":"Warsaw University of Technology","ror":"https://ror.org/00y0xnp53","country_code":"PL","type":"education","lineage":["https://openalex.org/I108403487"]}],"countries":["PL"],"is_corresponding":false,"raw_author_name":"Jordi Mongay Batalla","raw_affiliation_strings":["Warsaw University of Technology,Warsaw,Poland"],"affiliations":[{"raw_affiliation_string":"Warsaw University of Technology,Warsaw,Poland","institution_ids":["https://openalex.org/I108403487"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5030161759","display_name":"George Mastorakis","orcid":"https://orcid.org/0000-0002-6733-5652"},"institutions":[{"id":"https://openalex.org/I26840924","display_name":"Mediterranean University","ror":"https://ror.org/03tsjvt68","country_code":"ME","type":"education","lineage":["https://openalex.org/I26840924"]}],"countries":["ME"],"is_corresponding":false,"raw_author_name":"George Mastorakis","raw_affiliation_strings":["Hellenic Mediterranean University,Department of Management Science and Technology,Greece"],"affiliations":[{"raw_affiliation_string":"Hellenic Mediterranean University,Department of Management Science and Technology,Greece","institution_ids":["https://openalex.org/I26840924"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129854688","display_name":"Athina Bourdena","orcid":null},"institutions":[{"id":"https://openalex.org/I26840924","display_name":"Mediterranean University","ror":"https://ror.org/03tsjvt68","country_code":"ME","type":"education","lineage":["https://openalex.org/I26840924"]}],"countries":["ME"],"is_corresponding":false,"raw_author_name":"Athina Bourdena","raw_affiliation_strings":["Hellenic Mediterranean University,Department of Business Administration and Tourism,Heraklion,Greece"],"affiliations":[{"raw_affiliation_string":"Hellenic Mediterranean University,Department of Business Administration and Tourism,Heraklion,Greece","institution_ids":["https://openalex.org/I26840924"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5129783295","display_name":"Evangelos Markakis","orcid":null},"institutions":[{"id":"https://openalex.org/I28710699","display_name":"Hellenic Mediterranean University","ror":"https://ror.org/039ce0m20","country_code":"GR","type":"education","lineage":["https://openalex.org/I28710699"]}],"countries":["GR"],"is_corresponding":false,"raw_author_name":"Evangelos Markakis","raw_affiliation_strings":["Hellenic Mediterranean University,Department of Electrical and Computer Engineering,Heraklion,Greece"],"affiliations":[{"raw_affiliation_string":"Hellenic Mediterranean University,Department of Electrical and Computer Engineering,Heraklion,Greece","institution_ids":["https://openalex.org/I28710699"]}]}],"institutions":[],"countries_distinct_count":4,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5129984931"],"corresponding_institution_ids":["https://openalex.org/I17389662"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.79953214,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"4143","last_page":"4148"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10861","display_name":"Ear Surgery and Otitis Media","score":0.4246000051498413,"subfield":{"id":"https://openalex.org/subfields/2733","display_name":"Otorhinolaryngology"},"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/T10861","display_name":"Ear Surgery and Otitis Media","score":0.4246000051498413,"subfield":{"id":"https://openalex.org/subfields/2733","display_name":"Otorhinolaryngology"},"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/T10283","display_name":"Hearing Loss and Rehabilitation","score":0.10970000177621841,"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/T10860","display_name":"Speech and Audio Processing","score":0.04259999841451645,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6840999722480774},{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.6614999771118164},{"id":"https://openalex.org/keywords/preprocessor","display_name":"Preprocessor","score":0.6003999710083008},{"id":"https://openalex.org/keywords/hyperparameter","display_name":"Hyperparameter","score":0.5223000049591064},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5123999714851379},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.4584999978542328},{"id":"https://openalex.org/keywords/wiener-filter","display_name":"Wiener filter","score":0.4406999945640564},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.4101000130176544}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.775600016117096},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6840999722480774},{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.6614999771118164},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6011000275611877},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.6003999710083008},{"id":"https://openalex.org/C8642999","wikidata":"https://www.wikidata.org/wiki/Q4171168","display_name":"Hyperparameter","level":2,"score":0.5223000049591064},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5123999714851379},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.4584999978542328},{"id":"https://openalex.org/C18537770","wikidata":"https://www.wikidata.org/wiki/Q25523","display_name":"Wiener filter","level":2,"score":0.4406999945640564},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.414900004863739},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.4101000130176544},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.39750000834465027},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.39649999141693115},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.3847000002861023},{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.36090001463890076},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.3499000072479248},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.3427000045776367},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3370000123977661},{"id":"https://openalex.org/C55020928","wikidata":"https://www.wikidata.org/wiki/Q3813865","display_name":"Image quality","level":3,"score":0.323199987411499},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.2897999882698059},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2897999882698059},{"id":"https://openalex.org/C10485038","wikidata":"https://www.wikidata.org/wiki/Q48996162","display_name":"Hyperparameter optimization","level":3,"score":0.2574000060558319}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/globecom59602.2025.11432087","is_oa":false,"landing_page_url":"https://doi.org/10.1109/globecom59602.2025.11432087","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"GLOBECOM 2025 - 2025 IEEE Global Communications Conference","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":14,"referenced_works":["https://openalex.org/W3131478088","https://openalex.org/W4307342661","https://openalex.org/W4385564429","https://openalex.org/W4391690998","https://openalex.org/W4394893506","https://openalex.org/W4398249180","https://openalex.org/W4399198996","https://openalex.org/W4403355928","https://openalex.org/W4403998595","https://openalex.org/W4405912559","https://openalex.org/W4406765927","https://openalex.org/W4407520723","https://openalex.org/W4407936964","https://openalex.org/W4409954160"],"related_works":[],"abstract_inverted_index":{"The":[0,30,57,80],"proposed":[1],"system":[2],"known":[3],"as":[4],"Vision":[5],"Transformer-Masked":[6],"Autoencoder-Cheetah":[7],"Optimization":[8],"Algorithm":[9],"(ViT-MAE-COA)":[10],"uses":[11],"image":[12,35],"preprocessing":[13],"techniques":[14],"in":[15],"addition":[16],"to":[17,26,63],"segmentation":[18],"and":[19,22,50,68],"classification":[20],"features":[21],"hyperparameter":[23],"optimization":[24],"capabilities":[25],"classify":[27],"Otitis":[28],"Media.":[29],"framework":[31],"starts":[32],"by":[33],"improving":[34],"quality":[36],"through":[37,71],"the":[38,84],"Wiener":[39],"filter":[40],"(WF)":[41],"that":[42,74,83],"minimizes":[43],"mean":[44],"squared":[45],"error":[46],"between":[47],"original":[48],"images":[49,52],"noisy":[51],"for":[53],"noise":[54],"reduction":[55],"purposes.":[56],"W-Net":[58],"architecture":[59],"processes":[60],"segmented":[61],"data":[62,67],"maintain":[64],"essential":[65],"localization":[66],"content":[69],"information":[70],"a":[72],"strategy":[73],"decreases":[75],"parameters":[76],"with":[77],"max":[78],"pooling.":[79],"results":[81],"indicate":[82],"model":[85],"exhibited":[86],"better":[87],"prediction":[88],"accuracy":[89],"than":[90],"other":[91],"Deep":[92],"Learning":[93],"models.":[94]},"counts_by_year":[],"updated_date":"2026-03-20T20:54:20.808490","created_date":"2026-03-20T00:00:00"}
