{"id":"https://openalex.org/W4285163072","doi":"https://doi.org/10.1109/access.2022.3184694","title":"Out-of-Distribution Detection Based on Feature Fusion in Neural Network Classifier Pre-Trained by PEDCC-Loss","display_name":"Out-of-Distribution Detection Based on Feature Fusion in Neural Network Classifier Pre-Trained by PEDCC-Loss","publication_year":2022,"publication_date":"2022-01-01","ids":{"openalex":"https://openalex.org/W4285163072","doi":"https://doi.org/10.1109/access.2022.3184694"},"language":"en","primary_location":{"id":"doi:10.1109/access.2022.3184694","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2022.3184694","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/09801848.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/ielx7/6287639/6514899/09801848.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5028518753","display_name":"Qiuyu Zhu","orcid":"https://orcid.org/0000-0001-9514-9323"},"institutions":[{"id":"https://openalex.org/I113940042","display_name":"Shanghai University","ror":"https://ror.org/006teas31","country_code":"CN","type":"education","lineage":["https://openalex.org/I113940042"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Qiuyu Zhu","raw_affiliation_strings":["School of Communication and Information Engineering, Shanghai University, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0001-9514-9323","affiliations":[{"raw_affiliation_string":"School of Communication and Information Engineering, Shanghai University, Shanghai, China","institution_ids":["https://openalex.org/I113940042"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5044750780","display_name":"Guohui Zheng","orcid":"https://orcid.org/0000-0001-8114-1769"},"institutions":[{"id":"https://openalex.org/I113940042","display_name":"Shanghai University","ror":"https://ror.org/006teas31","country_code":"CN","type":"education","lineage":["https://openalex.org/I113940042"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guohui Zheng","raw_affiliation_strings":["School of Communication and Information Engineering, Shanghai University, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0001-8114-1769","affiliations":[{"raw_affiliation_string":"School of Communication and Information Engineering, Shanghai University, Shanghai, China","institution_ids":["https://openalex.org/I113940042"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101546712","display_name":"Jiakang Shen","orcid":"https://orcid.org/0000-0002-6083-8599"},"institutions":[{"id":"https://openalex.org/I113940042","display_name":"Shanghai University","ror":"https://ror.org/006teas31","country_code":"CN","type":"education","lineage":["https://openalex.org/I113940042"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiakang Shen","raw_affiliation_strings":["School of Communication and Information Engineering, Shanghai University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Communication and Information Engineering, Shanghai University, Shanghai, China","institution_ids":["https://openalex.org/I113940042"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100431313","display_name":"Rui Wang","orcid":"https://orcid.org/0000-0002-7974-9510"},"institutions":[{"id":"https://openalex.org/I113940042","display_name":"Shanghai University","ror":"https://ror.org/006teas31","country_code":"CN","type":"education","lineage":["https://openalex.org/I113940042"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Rui Wang","raw_affiliation_strings":["School of Communication and Information Engineering, Shanghai University, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0002-7974-9510","affiliations":[{"raw_affiliation_string":"School of Communication and Information Engineering, Shanghai University, Shanghai, China","institution_ids":["https://openalex.org/I113940042"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5028518753"],"corresponding_institution_ids":["https://openalex.org/I113940042"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":0.6944,"has_fulltext":true,"cited_by_count":5,"citation_normalized_percentile":{"value":0.74935888,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":"10","issue":null,"first_page":"66190","last_page":"66197"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9995999932289124,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9995999932289124,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9994000196456909,"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":0.9957000017166138,"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/computer-science","display_name":"Computer science","score":0.7968111634254456},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.7091831564903259},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6748978495597839},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.6489129662513733},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5382096767425537},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.47913357615470886},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.43492648005485535},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3965657949447632}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7968111634254456},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.7091831564903259},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6748978495597839},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.6489129662513733},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5382096767425537},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.47913357615470886},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.43492648005485535},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3965657949447632}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2022.3184694","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2022.3184694","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/09801848.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:d959b1839b9b4cada8be440000a39e86","is_oa":true,"landing_page_url":"https://doaj.org/article/d959b1839b9b4cada8be440000a39e86","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 10, Pp 66190-66197 (2022)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2022.3184694","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2022.3184694","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/09801848.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":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4285163072.pdf","grobid_xml":"https://content.openalex.org/works/W4285163072.grobid-xml"},"referenced_works_count":39,"referenced_works":["https://openalex.org/W967544008","https://openalex.org/W1751428553","https://openalex.org/W2001610032","https://openalex.org/W2062476635","https://openalex.org/W2108598243","https://openalex.org/W2126481981","https://openalex.org/W2135850590","https://openalex.org/W2158698691","https://openalex.org/W2194775991","https://openalex.org/W2531327146","https://openalex.org/W2535873859","https://openalex.org/W2759471388","https://openalex.org/W2767414122","https://openalex.org/W2784163702","https://openalex.org/W2786712888","https://openalex.org/W2914320670","https://openalex.org/W2963167203","https://openalex.org/W2963446712","https://openalex.org/W2964137095","https://openalex.org/W2970602317","https://openalex.org/W2981958729","https://openalex.org/W2995027615","https://openalex.org/W3034230713","https://openalex.org/W3103152812","https://openalex.org/W3118608800","https://openalex.org/W3157907018","https://openalex.org/W3183048323","https://openalex.org/W4223432309","https://openalex.org/W6625168331","https://openalex.org/W6637845589","https://openalex.org/W6687566353","https://openalex.org/W6728622933","https://openalex.org/W6739651123","https://openalex.org/W6745891213","https://openalex.org/W6748163547","https://openalex.org/W6752760542","https://openalex.org/W6759525204","https://openalex.org/W6773555910","https://openalex.org/W6787972765"],"related_works":["https://openalex.org/W2961085424","https://openalex.org/W2391251536","https://openalex.org/W2465918047","https://openalex.org/W2362198218","https://openalex.org/W2019521278","https://openalex.org/W1984922432","https://openalex.org/W2375008505","https://openalex.org/W2086348228","https://openalex.org/W2350679292","https://openalex.org/W1982750869"],"abstract_inverted_index":{"Out-of-distribution":[0],"(OOD)":[1],"detection":[2,22,71,93,122,153],"is":[3,67],"related":[4],"to":[5,35,72],"the":[6,16,26,42,50,53,77,96,104,107,114,120,157,162],"security":[7],"and":[8,45,138,155],"stability":[9],"of":[10,52,76,95,106,161],"deep":[11],"learning":[12],"models":[13],"deployed":[14],"in":[15,69,89],"real":[17],"world.":[18],"The":[19],"existing":[20,146],"OOD":[21,70,92,121,130,152],"algorithms":[23],"based":[24,59],"on":[25,60,134],"neural":[27,98],"network":[28,99,126],"normally":[29],"use":[30],"a":[31,85],"single":[32],"scoring":[33],"function":[34],"detect":[36],"out-of-distribution":[37],"examples,":[38],"which":[39,90,117],"start":[40],"from":[41],"posterior":[43],"probability":[44],"do":[46],"not":[47],"fully":[48],"utilize":[49],"information":[51],"pre-trained":[54,78],"model.":[55],"In":[56,110],"this":[57,148],"paper,":[58],"our":[61],"previous":[62],"PEDCC-based":[63,164],"work,":[64],"feature":[65],"fusion":[66],"explored":[68],"take":[73],"maximum":[74],"advantage":[75],"classifier":[79,100],"features.":[80],"Our":[81],"improved":[82],"method":[83,149],"adopts":[84],"two-stage":[86],"training":[87],"approach,":[88],"multiple":[91],"features":[94],"first-stage":[97],"are":[101],"extracted":[102],"as":[103],"input":[105],"second-stage":[108],"training.":[109],"addition,":[111],"we":[112],"propose":[113],"stop-near-saturation":[115],"method,":[116],"can":[118],"help":[119],"algorithm":[123],"find":[124],"optimal":[125],"parameters":[127],"without":[128],"accessing":[129],"data.":[131],"Extensive":[132],"experiments":[133],"several":[135],"public":[136],"datasets":[137],"classification":[139],"networks":[140],"show":[141],"that":[142],"compared":[143],"with":[144],"other":[145],"methods,":[147],"has":[150],"better":[151],"performance,":[154],"maintains":[156],"low":[158],"computational":[159],"complexity":[160],"original":[163],"method.":[165]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1}],"updated_date":"2026-05-06T08:25:59.206177","created_date":"2025-10-10T00:00:00"}
