{"id":"https://openalex.org/W2797061331","doi":"https://doi.org/10.1109/access.2018.2810849","title":"Improvement of Generalization Ability of Deep CNN via Implicit Regularization in Two-Stage Training Process","display_name":"Improvement of Generalization Ability of Deep CNN via Implicit Regularization in Two-Stage Training Process","publication_year":2018,"publication_date":"2018-01-01","ids":{"openalex":"https://openalex.org/W2797061331","doi":"https://doi.org/10.1109/access.2018.2810849","mag":"2797061331"},"language":"en","primary_location":{"id":"doi:10.1109/access.2018.2810849","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2018.2810849","pdf_url":null,"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://doi.org/10.1109/access.2018.2810849","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5102026679","display_name":"Qinghe Zheng","orcid":"https://orcid.org/0000-0003-1466-2542"},"institutions":[{"id":"https://openalex.org/I154099455","display_name":"Shandong University","ror":"https://ror.org/0207yh398","country_code":"CN","type":"education","lineage":["https://openalex.org/I154099455"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Qinghe Zheng","raw_affiliation_strings":["School of Information Science and Engineering, Shandong University, Jinan, China","ORCiD"],"affiliations":[{"raw_affiliation_string":"School of Information Science and Engineering, Shandong University, Jinan, China","institution_ids":["https://openalex.org/I154099455"]},{"raw_affiliation_string":"ORCiD","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101994934","display_name":"Mingqiang Yang","orcid":"https://orcid.org/0000-0002-7509-1256"},"institutions":[{"id":"https://openalex.org/I154099455","display_name":"Shandong University","ror":"https://ror.org/0207yh398","country_code":"CN","type":"education","lineage":["https://openalex.org/I154099455"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Mingqiang Yang","raw_affiliation_strings":["School of Information Science and Engineering, Shandong University, Jinan, China"],"affiliations":[{"raw_affiliation_string":"School of Information Science and Engineering, Shandong University, Jinan, China","institution_ids":["https://openalex.org/I154099455"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101684376","display_name":"Jiajie Yang","orcid":"https://orcid.org/0009-0002-9503-1813"},"institutions":[{"id":"https://openalex.org/I141945490","display_name":"University of British Columbia","ror":"https://ror.org/03rmrcq20","country_code":"CA","type":"education","lineage":["https://openalex.org/I141945490"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Jiajie Yang","raw_affiliation_strings":["Department of Science, The University of British Columbia, Vancouver, BC, Canada"],"affiliations":[{"raw_affiliation_string":"Department of Science, The University of British Columbia, Vancouver, BC, Canada","institution_ids":["https://openalex.org/I141945490"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5064825247","display_name":"Qingrui Zhang","orcid":"https://orcid.org/0000-0002-1733-159X"},"institutions":[{"id":"https://openalex.org/I154099455","display_name":"Shandong University","ror":"https://ror.org/0207yh398","country_code":"CN","type":"education","lineage":["https://openalex.org/I154099455"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qingrui Zhang","raw_affiliation_strings":["School of Information Science and Engineering, Shandong University, Jinan, China"],"affiliations":[{"raw_affiliation_string":"School of Information Science and Engineering, Shandong University, Jinan, China","institution_ids":["https://openalex.org/I154099455"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100375447","display_name":"Xinxin Zhang","orcid":"https://orcid.org/0000-0001-6069-5391"},"institutions":[{"id":"https://openalex.org/I154099455","display_name":"Shandong University","ror":"https://ror.org/0207yh398","country_code":"CN","type":"education","lineage":["https://openalex.org/I154099455"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xinxin Zhang","raw_affiliation_strings":["School of Information Science and Engineering, Shandong University, Jinan, China"],"affiliations":[{"raw_affiliation_string":"School of Information Science and Engineering, Shandong University, Jinan, China","institution_ids":["https://openalex.org/I154099455"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5102026679"],"corresponding_institution_ids":["https://openalex.org/I154099455"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":14.1984,"has_fulltext":false,"cited_by_count":259,"citation_normalized_percentile":{"value":0.9899069,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":100},"biblio":{"volume":"6","issue":null,"first_page":"15844","last_page":"15869"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":1.0,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":1.0,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9977999925613403,"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/T10400","display_name":"Network Security and Intrusion Detection","score":0.9858999848365784,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/overfitting","display_name":"Overfitting","score":0.8970547318458557},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7728097438812256},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7083187699317932},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.7054101824760437},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5297150611877441},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5114434957504272},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.46201860904693604},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4543534815311432},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4514086842536926},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4451940953731537},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.425864040851593},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.4130861163139343}],"concepts":[{"id":"https://openalex.org/C22019652","wikidata":"https://www.wikidata.org/wiki/Q331309","display_name":"Overfitting","level":3,"score":0.8970547318458557},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7728097438812256},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7083187699317932},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.7054101824760437},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5297150611877441},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5114434957504272},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.46201860904693604},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4543534815311432},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4514086842536926},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4451940953731537},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.425864040851593},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.4130861163139343},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2018.2810849","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2018.2810849","pdf_url":null,"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:5b21971076f744e58057ed2e864ea6a1","is_oa":true,"landing_page_url":"https://doaj.org/article/5b21971076f744e58057ed2e864ea6a1","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":"IEEE Access, Vol 6, Pp 15844-15869 (2018)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2018.2810849","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2018.2810849","pdf_url":null,"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":[{"id":"https://openalex.org/G3560273555","display_name":null,"funder_award_id":"ZR2014FM030","funder_id":"https://openalex.org/F4320324174","funder_display_name":"Natural Science Foundation of Shandong Province"},{"id":"https://openalex.org/G7106703725","display_name":null,"funder_award_id":"61571275","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320324174","display_name":"Natural Science Foundation of Shandong Province","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":95,"referenced_works":["https://openalex.org/W4919037","https://openalex.org/W101201821","https://openalex.org/W114517082","https://openalex.org/W187043655","https://openalex.org/W272277767","https://openalex.org/W639708223","https://openalex.org/W1521968289","https://openalex.org/W1522734439","https://openalex.org/W1524680991","https://openalex.org/W1533861849","https://openalex.org/W1554085250","https://openalex.org/W1664859298","https://openalex.org/W1677182931","https://openalex.org/W1686810756","https://openalex.org/W1690739335","https://openalex.org/W1694178301","https://openalex.org/W1703242834","https://openalex.org/W1821462560","https://openalex.org/W1836465849","https://openalex.org/W1904365287","https://openalex.org/W1907282891","https://openalex.org/W1971681701","https://openalex.org/W1974879849","https://openalex.org/W1993693225","https://openalex.org/W2003684104","https://openalex.org/W2056234582","https://openalex.org/W2061240327","https://openalex.org/W2095345875","https://openalex.org/W2097117768","https://openalex.org/W2107215754","https://openalex.org/W2112796928","https://openalex.org/W2117539524","https://openalex.org/W2124372976","https://openalex.org/W2127979711","https://openalex.org/W2129281431","https://openalex.org/W2132424367","https://openalex.org/W2132870739","https://openalex.org/W2138857742","https://openalex.org/W2140650410","https://openalex.org/W2145607950","https://openalex.org/W2155541015","https://openalex.org/W2168894214","https://openalex.org/W2204904589","https://openalex.org/W2236497445","https://openalex.org/W2253535400","https://openalex.org/W2294059674","https://openalex.org/W2335728318","https://openalex.org/W2345094839","https://openalex.org/W2345474290","https://openalex.org/W2408701322","https://openalex.org/W2467640454","https://openalex.org/W2509818455","https://openalex.org/W2547788783","https://openalex.org/W2553902701","https://openalex.org/W2570903723","https://openalex.org/W2602844676","https://openalex.org/W2618530766","https://openalex.org/W2763318011","https://openalex.org/W2765833400","https://openalex.org/W2766447205","https://openalex.org/W2766956386","https://openalex.org/W2950495522","https://openalex.org/W2950621961","https://openalex.org/W2962835968","https://openalex.org/W2963037478","https://openalex.org/W2963574257","https://openalex.org/W2963919294","https://openalex.org/W2964118293","https://openalex.org/W3118338202","https://openalex.org/W3118608800","https://openalex.org/W3137695714","https://openalex.org/W4253461361","https://openalex.org/W4294375521","https://openalex.org/W4295126650","https://openalex.org/W4300537377","https://openalex.org/W6600213771","https://openalex.org/W6607543680","https://openalex.org/W6620707391","https://openalex.org/W6626481562","https://openalex.org/W6631943919","https://openalex.org/W6638667902","https://openalex.org/W6676231585","https://openalex.org/W6680300913","https://openalex.org/W6680946154","https://openalex.org/W6682778277","https://openalex.org/W6684665197","https://openalex.org/W6684704092","https://openalex.org/W6685315510","https://openalex.org/W6688902765","https://openalex.org/W6696761078","https://openalex.org/W6703116779","https://openalex.org/W6719772885","https://openalex.org/W6745086892","https://openalex.org/W6763485134","https://openalex.org/W6787972765"],"related_works":["https://openalex.org/W4362597605","https://openalex.org/W1574414179","https://openalex.org/W4297676672","https://openalex.org/W3009056573","https://openalex.org/W2922073769","https://openalex.org/W4281702477","https://openalex.org/W2490526372","https://openalex.org/W4376166922","https://openalex.org/W4378510483","https://openalex.org/W4221142204"],"abstract_inverted_index":{"Optimization":[0],"of":[1,19,57,85,187],"deep":[2,58,86],"learning":[3],"is":[4,45,48],"no":[5],"longer":[6],"an":[7,49],"imminent":[8],"problem,":[9],"due":[10],"to":[11,52,65,80,100,114,138,189],"various":[12],"gradient":[13],"descent":[14],"methods":[15],"and":[16,28,95,143,168,191,216],"the":[17,25,32,37,54,82,102,106,116,123,130,134,140,148,160,200],"improvements":[18],"network":[20,44,112,131],"structure,":[21],"including":[22],"activation":[23],"functions,":[24],"connectivity":[26],"style,":[27],"so":[29],"on.":[30],"Then":[31],"actual":[33],"application":[34],"depends":[35],"on":[36,133,153],"generalization":[38,55],"ability,":[39],"which":[40],"determines":[41],"whether":[42],"a":[43,72,89,111,165,185,197],"effective.":[46],"Regularization":[47],"efficient":[50],"way":[51],"improve":[53],"ability":[56],"CNN,":[59],"because":[60],"it":[61,63,145],"makes":[62],"possible":[64],"train":[66,110],"more":[67,174],"complex":[68],"models":[69],"while":[70],"maintaining":[71],"lower":[73],"overfitting.":[74],"In":[75,105,122],"this":[76],"paper,":[77],"we":[78,109,128,183,205],"propose":[79],"optimize":[81],"feature":[83,141],"boundary":[84,142],"CNN":[87],"through":[88],"two-stage":[90,161,201],"training":[91,98,126,162,202],"method":[92,163],"(pre-training":[93],"process":[94],"implicit":[96,124,194,208],"regularization":[97,125,195,209],"process)":[99],"reduce":[101],"overfitting":[103],"problem.":[104],"pre-training":[107],"stage,":[108,127],"model":[113,217],"extract":[115],"image":[117,155],"representation":[118],"for":[119],"anomaly":[120,135,176],"detection.":[121],"re-train":[129],"based":[132],"detection":[136,177],"results":[137,152],"regularize":[139],"make":[144],"converge":[146],"in":[147,171,199],"proper":[149],"position.":[150],"Experimental":[151],"five":[154],"classification":[156],"benchmarks":[157],"show":[158],"that":[159,169],"achieves":[164],"state-of-the-art":[166],"performance":[167],"it,":[170],"conjunction":[172],"with":[173],"complicated":[175],"algorithm,":[178],"obtains":[179],"better":[180],"results.":[181],"Finally,":[182],"use":[184],"variety":[186],"strategies":[188],"explore":[190],"analyze":[192],"how":[193,207],"plays":[196],"role":[198],"process.":[203],"Furthermore,":[204],"explain":[206],"can":[210],"be":[211],"interpreted":[212],"as":[213],"data":[214],"augmentation":[215],"ensemble.":[218]},"counts_by_year":[{"year":2026,"cited_by_count":4},{"year":2025,"cited_by_count":19},{"year":2024,"cited_by_count":14},{"year":2023,"cited_by_count":52},{"year":2022,"cited_by_count":86},{"year":2021,"cited_by_count":42},{"year":2020,"cited_by_count":25},{"year":2019,"cited_by_count":14},{"year":2018,"cited_by_count":3}],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}
