{"id":"https://openalex.org/W4400066725","doi":"https://doi.org/10.1145/3663976.3663992","title":"Stacking algorithm based on naive Bayes","display_name":"Stacking algorithm based on naive Bayes","publication_year":2024,"publication_date":"2024-04-26","ids":{"openalex":"https://openalex.org/W4400066725","doi":"https://doi.org/10.1145/3663976.3663992"},"language":"en","primary_location":{"id":"doi:10.1145/3663976.3663992","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3663976.3663992","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2024 2nd Asia Conference on Computer Vision, Image Processing and Pattern Recognition","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/A5102958220","display_name":"Chen Huang","orcid":"https://orcid.org/0009-0005-6196-7981"},"institutions":[{"id":"https://openalex.org/I184983240","display_name":"Northeast Normal University","ror":"https://ror.org/02rkvz144","country_code":"CN","type":"education","lineage":["https://openalex.org/I184983240"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chen Huang","raw_affiliation_strings":["Academy for Advanced Interdisciplinary Studies, Northeast Normal University, China and \rBeijing Institute of Remote Sensing, China"],"raw_orcid":"https://orcid.org/0009-0005-6196-7981","affiliations":[{"raw_affiliation_string":"Academy for Advanced Interdisciplinary Studies, Northeast Normal University, China and \rBeijing Institute of Remote Sensing, China","institution_ids":["https://openalex.org/I184983240"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5098716716","display_name":"Yuting Zhou","orcid":"https://orcid.org/0009-0003-0792-3115"},"institutions":[{"id":"https://openalex.org/I40246663","display_name":"Chinese Academy of Engineering","ror":"https://ror.org/00z3yke57","country_code":"CN","type":"other","lineage":["https://openalex.org/I40246663"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuting Zhou","raw_affiliation_strings":["Computational Mathematics, Chinese Academy of Engineering Physics, China"],"raw_orcid":"https://orcid.org/0009-0003-0792-3115","affiliations":[{"raw_affiliation_string":"Computational Mathematics, Chinese Academy of Engineering Physics, China","institution_ids":["https://openalex.org/I40246663"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5018230009","display_name":"Xuemei Yang","orcid":"https://orcid.org/0009-0002-1298-6877"},"institutions":[{"id":"https://openalex.org/I40246663","display_name":"Chinese Academy of Engineering","ror":"https://ror.org/00z3yke57","country_code":"CN","type":"other","lineage":["https://openalex.org/I40246663"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xuemei Yang","raw_affiliation_strings":["Computational Mathematics, Chinese Academy of Engineering Physics, China"],"raw_orcid":"https://orcid.org/0009-0002-1298-6877","affiliations":[{"raw_affiliation_string":"Computational Mathematics, Chinese Academy of Engineering Physics, China","institution_ids":["https://openalex.org/I40246663"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5106406744","display_name":"Shiqi Liu","orcid":"https://orcid.org/0000-0002-0578-4321"},"institutions":[{"id":"https://openalex.org/I40246663","display_name":"Chinese Academy of Engineering","ror":"https://ror.org/00z3yke57","country_code":"CN","type":"other","lineage":["https://openalex.org/I40246663"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shiqi Liu","raw_affiliation_strings":["Computational Mathematics, Chinese Academy of Engineering Physics, China"],"raw_orcid":"https://orcid.org/0000-0002-0578-4321","affiliations":[{"raw_affiliation_string":"Computational Mathematics, Chinese Academy of Engineering Physics, China","institution_ids":["https://openalex.org/I40246663"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101678893","display_name":"Junping Yin","orcid":"https://orcid.org/0000-0002-9270-2071"},"institutions":[{"id":"https://openalex.org/I4210145278","display_name":"Institute of Applied Physics and Computational Mathematics","ror":"https://ror.org/03sxpbt26","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210145278"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Junping Yin","raw_affiliation_strings":["Big Data Center, Beijing Institute of Applied Physics and Computational Mathematics, China"],"raw_orcid":"https://orcid.org/0000-0002-9270-2071","affiliations":[{"raw_affiliation_string":"Big Data Center, Beijing Institute of Applied Physics and Computational Mathematics, China","institution_ids":["https://openalex.org/I4210145278"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"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":0.11710782,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.9987999796867371,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.9987999796867371,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12549","display_name":"Image and Object Detection Techniques","score":0.9962000250816345,"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/T10638","display_name":"Optical measurement and interference techniques","score":0.9922000169754028,"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/naive-bayes-classifier","display_name":"Naive Bayes classifier","score":0.7496187090873718},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7091602087020874},{"id":"https://openalex.org/keywords/stacking","display_name":"Stacking","score":0.5854589939117432},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5117006301879883},{"id":"https://openalex.org/keywords/bayes-theorem","display_name":"Bayes' theorem","score":0.4608878791332245},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3961370587348938},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.32141944766044617},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.1058589518070221}],"concepts":[{"id":"https://openalex.org/C52001869","wikidata":"https://www.wikidata.org/wiki/Q812530","display_name":"Naive Bayes classifier","level":3,"score":0.7496187090873718},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7091602087020874},{"id":"https://openalex.org/C33347731","wikidata":"https://www.wikidata.org/wiki/Q285210","display_name":"Stacking","level":2,"score":0.5854589939117432},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5117006301879883},{"id":"https://openalex.org/C207201462","wikidata":"https://www.wikidata.org/wiki/Q182505","display_name":"Bayes' theorem","level":3,"score":0.4608878791332245},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3961370587348938},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.32141944766044617},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.1058589518070221},{"id":"https://openalex.org/C46141821","wikidata":"https://www.wikidata.org/wiki/Q209402","display_name":"Nuclear magnetic resonance","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3663976.3663992","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3663976.3663992","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2024 2nd Asia Conference on Computer Vision, Image Processing and Pattern Recognition","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":5,"referenced_works":["https://openalex.org/W2581082771","https://openalex.org/W2767512561","https://openalex.org/W2794583167","https://openalex.org/W3007170347","https://openalex.org/W3138476267"],"related_works":["https://openalex.org/W2035329725","https://openalex.org/W4376641153","https://openalex.org/W2070875936","https://openalex.org/W4250391473","https://openalex.org/W3045075405","https://openalex.org/W4302292679","https://openalex.org/W4241625287","https://openalex.org/W2050788868","https://openalex.org/W2537862391","https://openalex.org/W2417174640"],"abstract_inverted_index":{"With":[0],"the":[1,4,38,51,54,57,64,67,76,81,94,104,107,113,116,123,127,147,152,176,185,190,197,215],"advent":[2],"of":[3,47,56,66,75,106,115,201],"data":[5,9],"era,":[6],"medical":[7,48,202],"image":[8,164],"plays":[10],"an":[11],"increasingly":[12],"important":[13],"role":[14],"in":[15,100],"diagnosing":[16],"and":[17,27,63,112,130,156,160,175,204,214],"treating":[18],"diseases.":[19],"This":[20],"study":[21],"combined":[22],"deep":[23],"learning,":[24,26],"ensemble":[25],"mathematical":[28],"theory":[29],"to":[30,42,139],"construct":[31,140],"a":[32,89,141,171,210],"Stacking":[33,52,90,143,178,186,217],"algorithm":[34,91,144,153,187],"model":[35],"based":[36,92,145,188],"on":[37,93,146,189],"Naive":[39,95,148,191],"Bayes":[40,96,149,192],"method":[41,97,193],"achieve":[43],"more":[44],"accurate":[45],"classification":[46,83,199,207],"images.":[49],"In":[50],"algorithm,":[53],"results":[55,182,208],"primary":[58,68,77,108,117,137,173,212],"classifier":[59,69,78,109,118,174,213],"are":[60],"treated":[61],"equally,":[62],"performance":[65,74,105],"is":[70,98,110,119,168,194],"ignored.":[71],"The":[72,180],"poor":[73],"will":[79],"affect":[80],"final":[82],"result.":[84],"To":[85],"solve":[86],"this":[87,101],"problem,":[88],"proposed":[99],"paper.":[102],"Firstly,":[103],"evaluated,":[111],"output":[114],"selected":[120],"reasonably":[121],"through":[122],"evaluation":[124],"results.":[125],"Secondly,":[126],"VGGNet,":[128],"InceptionNet,":[129],"ResNet":[131],"convolutional":[132],"networks":[133],"were":[134],"used":[135],"as":[136],"classifiers":[138],"complete":[142],"method.":[150],"Next,":[151],"was":[154],"tested":[155],"validated":[157],"using":[158],"COVID-19":[159],"NoCOVID-19":[161],"lung":[162],"CT":[163],"data.":[165],"Finally,":[166],"it":[167],"compared":[169],"with":[170],"single":[172,211],"traditional":[177,216],"algorithm.":[179,218],"experimental":[181],"show":[183],"that":[184],"suitable":[195],"for":[196],"binary":[198],"task":[200],"images":[203],"has":[205],"better":[206],"than":[209]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}