{"id":"https://openalex.org/W3115656130","doi":"https://doi.org/10.3390/s21010122","title":"AF-SENet: Classification of Cancer in Cervical Tissue Pathological Images Based on Fusing Deep Convolution Features","display_name":"AF-SENet: Classification of Cancer in Cervical Tissue Pathological Images Based on Fusing Deep Convolution Features","publication_year":2020,"publication_date":"2020-12-27","ids":{"openalex":"https://openalex.org/W3115656130","doi":"https://doi.org/10.3390/s21010122","mag":"3115656130","pmid":"https://pubmed.ncbi.nlm.nih.gov/33375508"},"language":"en","primary_location":{"id":"doi:10.3390/s21010122","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s21010122","pdf_url":"https://www.mdpi.com/1424-8220/21/1/122/pdf?version=1609748765","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/1424-8220/21/1/122/pdf?version=1609748765","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5037654021","display_name":"Pan Huang","orcid":"https://orcid.org/0000-0001-8158-2628"},"institutions":[{"id":"https://openalex.org/I158842170","display_name":"Chongqing University","ror":"https://ror.org/023rhb549","country_code":"CN","type":"education","lineage":["https://openalex.org/I158842170"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Pan Huang","raw_affiliation_strings":["School of Microelectronics and Communication Engineering, Chongqing University, Chongqing 400044, China"],"affiliations":[{"raw_affiliation_string":"School of Microelectronics and Communication Engineering, Chongqing University, Chongqing 400044, China","institution_ids":["https://openalex.org/I158842170"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101699209","display_name":"Xiaoheng Tan","orcid":"https://orcid.org/0000-0001-9376-4920"},"institutions":[{"id":"https://openalex.org/I158842170","display_name":"Chongqing University","ror":"https://ror.org/023rhb549","country_code":"CN","type":"education","lineage":["https://openalex.org/I158842170"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaoheng Tan","raw_affiliation_strings":["School of Microelectronics and Communication Engineering, Chongqing University, Chongqing 400044, China"],"affiliations":[{"raw_affiliation_string":"School of Microelectronics and Communication Engineering, Chongqing University, Chongqing 400044, China","institution_ids":["https://openalex.org/I158842170"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100418543","display_name":"Chen Chen","orcid":"https://orcid.org/0000-0003-1406-5721"},"institutions":[{"id":"https://openalex.org/I96908189","display_name":"Xinjiang University","ror":"https://ror.org/059gw8r13","country_code":"CN","type":"education","lineage":["https://openalex.org/I96908189"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chen Chen","raw_affiliation_strings":["School of Information Science and Engineering, Xinjiang University, \u00dcr\u00fcmqi 830046, China"],"affiliations":[{"raw_affiliation_string":"School of Information Science and Engineering, Xinjiang University, \u00dcr\u00fcmqi 830046, China","institution_ids":["https://openalex.org/I96908189"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5113381584","display_name":"Xiaoyi Lv","orcid":null},"institutions":[{"id":"https://openalex.org/I96908189","display_name":"Xinjiang University","ror":"https://ror.org/059gw8r13","country_code":"CN","type":"education","lineage":["https://openalex.org/I96908189"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaoyi Lv","raw_affiliation_strings":["College of Software, Xinjiang University, \u00dcr\u00fcmqi 830046, China"],"affiliations":[{"raw_affiliation_string":"College of Software, Xinjiang University, \u00dcr\u00fcmqi 830046, China","institution_ids":["https://openalex.org/I96908189"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5106920582","display_name":"Yongming Li","orcid":"https://orcid.org/0000-0002-7542-4356"},"institutions":[{"id":"https://openalex.org/I158842170","display_name":"Chongqing University","ror":"https://ror.org/023rhb549","country_code":"CN","type":"education","lineage":["https://openalex.org/I158842170"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yongming Li","raw_affiliation_strings":["School of Microelectronics and Communication Engineering, Chongqing University, Chongqing 400044, China"],"affiliations":[{"raw_affiliation_string":"School of Microelectronics and Communication Engineering, Chongqing University, Chongqing 400044, China","institution_ids":["https://openalex.org/I158842170"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5037654021"],"corresponding_institution_ids":["https://openalex.org/I158842170"],"apc_list":{"value":2400,"currency":"CHF","value_usd":2598},"apc_paid":{"value":2400,"currency":"CHF","value_usd":2598},"fwci":3.5655,"has_fulltext":false,"cited_by_count":50,"citation_normalized_percentile":{"value":0.94154291,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":100},"biblio":{"volume":"21","issue":"1","first_page":"122","last_page":"122"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10862","display_name":"AI in cancer detection","score":0.9998000264167786,"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":0.9998000264167786,"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/T10146","display_name":"Cervical Cancer and HPV Research","score":0.994700014591217,"subfield":{"id":"https://openalex.org/subfields/2713","display_name":"Epidemiology"},"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/T12422","display_name":"Radiomics and Machine Learning in Medical Imaging","score":0.9943000078201294,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7495259642601013},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.7349305152893066},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6044586300849915},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5816649198532104},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5177080631256104},{"id":"https://openalex.org/keywords/multispectral-image","display_name":"Multispectral image","score":0.4863646626472473},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.45994848012924194},{"id":"https://openalex.org/keywords/histogram","display_name":"Histogram","score":0.45514705777168274},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.43111586570739746},{"id":"https://openalex.org/keywords/medical-diagnosis","display_name":"Medical diagnosis","score":0.4133543372154236},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.2336098551750183},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.21976548433303833},{"id":"https://openalex.org/keywords/pathology","display_name":"Pathology","score":0.21553727984428406},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.19686660170555115}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7495259642601013},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.7349305152893066},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6044586300849915},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5816649198532104},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5177080631256104},{"id":"https://openalex.org/C173163844","wikidata":"https://www.wikidata.org/wiki/Q1761440","display_name":"Multispectral image","level":2,"score":0.4863646626472473},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.45994848012924194},{"id":"https://openalex.org/C53533937","wikidata":"https://www.wikidata.org/wiki/Q185020","display_name":"Histogram","level":3,"score":0.45514705777168274},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.43111586570739746},{"id":"https://openalex.org/C534262118","wikidata":"https://www.wikidata.org/wiki/Q177719","display_name":"Medical diagnosis","level":2,"score":0.4133543372154236},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.2336098551750183},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.21976548433303833},{"id":"https://openalex.org/C142724271","wikidata":"https://www.wikidata.org/wiki/Q7208","display_name":"Pathology","level":1,"score":0.21553727984428406},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.19686660170555115}],"mesh":[{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D002583","descriptor_name":"Uterine Cervical Neoplasms","qualifier_ui":"Q000000981","qualifier_name":"diagnostic imaging","is_major_topic":true},{"descriptor_ui":"D002583","descriptor_name":"Uterine Cervical Neoplasms","qualifier_ui":"Q000000981","qualifier_name":"diagnostic imaging","is_major_topic":true},{"descriptor_ui":"D002583","descriptor_name":"Uterine Cervical Neoplasms","qualifier_ui":"Q000000981","qualifier_name":"diagnostic imaging","is_major_topic":true},{"descriptor_ui":"D002583","descriptor_name":"Uterine Cervical Neoplasms","qualifier_ui":"Q000473","qualifier_name":"pathology","is_major_topic":true},{"descriptor_ui":"D002583","descriptor_name":"Uterine Cervical Neoplasms","qualifier_ui":"Q000473","qualifier_name":"pathology","is_major_topic":true},{"descriptor_ui":"D002583","descriptor_name":"Uterine Cervical Neoplasms","qualifier_ui":"Q000473","qualifier_name":"pathology","is_major_topic":true},{"descriptor_ui":"D005260","descriptor_name":"Female","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D005260","descriptor_name":"Female","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D005260","descriptor_name":"Female","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D007091","descriptor_name":"Image Processing, Computer-Assisted","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D007091","descriptor_name":"Image Processing, Computer-Assisted","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D007091","descriptor_name":"Image Processing, Computer-Assisted","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true}],"locations_count":6,"locations":[{"id":"doi:10.3390/s21010122","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s21010122","pdf_url":"https://www.mdpi.com/1424-8220/21/1/122/pdf?version=1609748765","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},{"id":"pmid:33375508","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/33375508","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors (Basel, Switzerland)","raw_type":null},{"id":"pmh:oai:doaj.org/article:cabc5d4c84c7421e9212c0aaddf51444","is_oa":true,"landing_page_url":"https://doaj.org/article/cabc5d4c84c7421e9212c0aaddf51444","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Sensors, Vol 21, Iss 1, p 122 (2020)","raw_type":"article"},{"id":"pmh:oai:europepmc.org:6704740","is_oa":true,"landing_page_url":"http://europepmc.org/pmc/articles/PMC7795214","pdf_url":null,"source":{"id":"https://openalex.org/S4306400806","display_name":"Europe PMC (PubMed Central)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1303153112","host_organization_name":"European Bioinformatics Institute","host_organization_lineage":["https://openalex.org/I1303153112"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Text"},{"id":"pmh:oai:mdpi.com:/1424-8220/21/1/122/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/s21010122","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Sensors; Volume 21; Issue 1; Pages: 122","raw_type":"Text"},{"id":"pmh:oai:pubmedcentral.nih.gov:7795214","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/7795214","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Sensors (Basel)","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/s21010122","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s21010122","pdf_url":"https://www.mdpi.com/1424-8220/21/1/122/pdf?version=1609748765","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education","score":0.6800000071525574}],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3115656130.pdf","grobid_xml":"https://content.openalex.org/works/W3115656130.grobid-xml"},"referenced_works_count":43,"referenced_works":["https://openalex.org/W204268067","https://openalex.org/W1849277567","https://openalex.org/W2027123781","https://openalex.org/W2100495367","https://openalex.org/W2103243046","https://openalex.org/W2108598243","https://openalex.org/W2112796928","https://openalex.org/W2122585011","https://openalex.org/W2136922672","https://openalex.org/W2139754658","https://openalex.org/W2202325181","https://openalex.org/W2288559628","https://openalex.org/W2343051383","https://openalex.org/W2417089552","https://openalex.org/W2601206107","https://openalex.org/W2618999197","https://openalex.org/W2621792616","https://openalex.org/W2767040509","https://openalex.org/W2902315714","https://openalex.org/W2909431490","https://openalex.org/W2914337210","https://openalex.org/W2947159644","https://openalex.org/W2962719749","https://openalex.org/W2963896025","https://openalex.org/W2971376088","https://openalex.org/W2979001271","https://openalex.org/W2981808298","https://openalex.org/W2982100822","https://openalex.org/W2987703048","https://openalex.org/W3003581523","https://openalex.org/W3007562589","https://openalex.org/W3015543711","https://openalex.org/W3025102114","https://openalex.org/W3030889987","https://openalex.org/W3032833225","https://openalex.org/W3033382446","https://openalex.org/W3033554993","https://openalex.org/W3045942182","https://openalex.org/W3046154346","https://openalex.org/W3048101421","https://openalex.org/W3054552769","https://openalex.org/W3097992810","https://openalex.org/W6687785150"],"related_works":["https://openalex.org/W4318664220","https://openalex.org/W2771047279","https://openalex.org/W4388409104","https://openalex.org/W2124951708","https://openalex.org/W1544811710","https://openalex.org/W172072032","https://openalex.org/W2006066416","https://openalex.org/W3157073418","https://openalex.org/W2021642829","https://openalex.org/W2058127401"],"abstract_inverted_index":{"Cervical":[0],"cancer":[1,7],"is":[2,155,201,227,237,251,260],"the":[3,9,19,32,39,44,49,84,114,125,129,137,143,161,167,184,218,228,276],"fourth":[4],"most":[5],"common":[6],"in":[8,35,149,255],"world.":[10],"Whole-slide":[11],"images":[12,182],"(WSIs)":[13],"are":[14,88,122,132,164,178],"an":[15,76],"important":[16],"standard":[17],"for":[18,80,157,175],"diagnosis":[20],"of":[21,42,53,113,145,169,183,217,281],"cervical":[22,37,283],"cancer.":[23,198],"Missed":[24],"diagnoses":[25],"and":[26,48,61,64,103,105,110,142,152,197,208,224,243,266,278],"misdiagnoses":[27],"often":[28],"occur":[29],"due":[30],"to":[31,117,136],"high":[33],"similarity":[34],"pathological":[36,69,181,282],"images,":[38],"large":[40],"number":[41],"readings,":[43],"long":[45],"reading":[46],"time,":[47],"insufficient":[50,58,68],"experience":[51],"levels":[52],"pathologists.":[54],"Existing":[55],"models":[56,131],"have":[57],"feature":[59,138],"extraction":[60],"representation":[62,139],"capabilities,":[63],"they":[65],"suffer":[66],"from":[67],"classification.":[70,176],"Therefore,":[71],"this":[72,150,272],"work":[73],"first":[74],"designs":[75],"image":[77,120],"processing":[78],"algorithm":[79],"data":[81],"augmentation.":[82],"Second,":[83],"deep":[85,93,219,288],"convolutional":[86],"features":[87,121,126,163,220],"extracted":[89,127,221],"by":[90,128,222,286],"fine-tuning":[91],"pre-trained":[92],"network":[94],"models,":[95],"including":[96],"ResNet50":[97,241,264],"v2,":[98],"DenseNet121,":[99],"Inception":[100],"v3,":[101],"VGGNet19,":[102],"Inception-ResNet,":[104],"then":[106],"local":[107],"binary":[108],"patterns":[109],"a":[111,204,209],"histogram":[112],"oriented":[115],"gradient":[116],"extract":[118],"traditional":[119],"used.":[123],"Third,":[124],"fine-tuned":[130],"serially":[133],"fused":[134,162],"according":[135],"ability":[140,250,280],"parameters":[141],"accuracy":[144,233,277],"multiple":[146],"experiments":[147],"proposed":[148],"paper,":[151],"spectral":[153],"embedding":[154],"used":[156],"dimension":[158],"reduction.":[159],"Finally,":[160],"inputted":[165],"into":[166,203],"Analysis":[168],"Variance-F":[170],"value-Spectral":[171],"Embedding":[172],"Net":[173],"(AF-SENet)":[174],"There":[177],"four":[179],"different":[180],"dataset:":[185],"normal,":[186],"low-grade":[187],"squamous":[188,193],"intraepithelial":[189,194],"lesion":[190,195],"(LSIL),":[191],"high-grade":[192],"(HSIL),":[196],"The":[199,213,248],"dataset":[200],"divided":[202],"training":[205],"set":[206,211],"(90%)":[207],"test":[210],"(10%).":[212],"serial":[214],"fusion":[215],"effect":[216],"Resnet50v2":[223],"DenseNet121":[225],"()":[226],"best,":[229],"with":[230],"average":[231],"classification":[232],"reaching":[234,257],"95.33%,":[235],"which":[236,259],"1.07%":[238],"higher":[239,245,262,268],"than":[240,246,263,269],"v2":[242,265],"1.05%":[244],"DenseNet121.":[247,270],"recognition":[249,285],"significantly":[252,274],"improved,":[253],"especially":[254],"LSIL,":[256],"90.89%,":[258],"2.88%":[261],"2.1%":[267],"Thus,":[271],"method":[273],"improves":[275],"generalization":[279],"WSI":[284],"fusing":[287],"features.":[289]},"counts_by_year":[{"year":2025,"cited_by_count":9},{"year":2024,"cited_by_count":15},{"year":2023,"cited_by_count":14},{"year":2022,"cited_by_count":7},{"year":2021,"cited_by_count":5}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2025-10-10T00:00:00"}