{"id":"https://openalex.org/W2903047678","doi":"https://doi.org/10.1109/icpr.2018.8545535","title":"Retraining: A Simple Way to Improve the Ensemble Accuracy of Deep Neural Networks for Image Classification","display_name":"Retraining: A Simple Way to Improve the Ensemble Accuracy of Deep Neural Networks for Image Classification","publication_year":2018,"publication_date":"2018-08-01","ids":{"openalex":"https://openalex.org/W2903047678","doi":"https://doi.org/10.1109/icpr.2018.8545535","mag":"2903047678"},"language":"en","primary_location":{"id":"doi:10.1109/icpr.2018.8545535","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr.2018.8545535","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 24th International Conference on Pattern Recognition (ICPR)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5021720283","display_name":"Kaikai Zhao","orcid":"https://orcid.org/0000-0002-6362-1352"},"institutions":[{"id":"https://openalex.org/I135598925","display_name":"Kyushu University","ror":"https://ror.org/00p4k0j84","country_code":"JP","type":"education","lineage":["https://openalex.org/I135598925"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Kaikai Zhao","raw_affiliation_strings":["Graduate School of Systems Life Sciences, Kyushu University, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Graduate School of Systems Life Sciences, Kyushu University, Japan","institution_ids":["https://openalex.org/I135598925"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5090155504","display_name":"Tetsu Matsukawa","orcid":"https://orcid.org/0000-0002-8841-6304"},"institutions":[{"id":"https://openalex.org/I135598925","display_name":"Kyushu University","ror":"https://ror.org/00p4k0j84","country_code":"JP","type":"education","lineage":["https://openalex.org/I135598925"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Tetsu Matsukawa","raw_affiliation_strings":["Department of Informatics, ISEE Kyushu University, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Informatics, ISEE Kyushu University, Japan","institution_ids":["https://openalex.org/I135598925"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5049568882","display_name":"Einoshin Suzuki","orcid":"https://orcid.org/0000-0001-7743-6177"},"institutions":[{"id":"https://openalex.org/I135598925","display_name":"Kyushu University","ror":"https://ror.org/00p4k0j84","country_code":"JP","type":"education","lineage":["https://openalex.org/I135598925"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Einoshin Suzuki","raw_affiliation_strings":["Department of Informatics, ISEE Kyushu University, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Informatics, ISEE Kyushu University, Japan","institution_ids":["https://openalex.org/I135598925"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I135598925"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":11,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"860","last_page":"867"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.996999979019165,"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":0.996999979019165,"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":0.9968000054359436,"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/T12535","display_name":"Machine Learning and Data Classification","score":0.9962999820709229,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/retraining","display_name":"Retraining","score":0.7255954742431641},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7066383957862854},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.695392370223999},{"id":"https://openalex.org/keywords/simple","display_name":"Simple (philosophy)","score":0.6570193767547607},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5830783843994141},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.5200576186180115},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4878716468811035},{"id":"https://openalex.org/keywords/deep-neural-networks","display_name":"Deep neural networks","score":0.4789731502532959},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4387480914592743},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4217250943183899},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4147055447101593}],"concepts":[{"id":"https://openalex.org/C2778712577","wikidata":"https://www.wikidata.org/wiki/Q3505966","display_name":"Retraining","level":2,"score":0.7255954742431641},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7066383957862854},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.695392370223999},{"id":"https://openalex.org/C2780586882","wikidata":"https://www.wikidata.org/wiki/Q7520643","display_name":"Simple (philosophy)","level":2,"score":0.6570193767547607},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5830783843994141},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.5200576186180115},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4878716468811035},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.4789731502532959},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4387480914592743},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4217250943183899},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4147055447101593},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C155202549","wikidata":"https://www.wikidata.org/wiki/Q178803","display_name":"International trade","level":1,"score":0.0},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icpr.2018.8545535","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr.2018.8545535","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 24th International Conference on Pattern Recognition (ICPR)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2852091844","display_name":"Anomalous/Exceptional Pattern Mining with Weak Label Information from Stream Data","funder_award_id":"18H03290","funder_id":"https://openalex.org/F4320334764","funder_display_name":"Japan Society for the Promotion of Science"}],"funders":[{"id":"https://openalex.org/F4320334764","display_name":"Japan Society for the Promotion of Science","ror":"https://ror.org/00hhkn466"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":52,"referenced_works":["https://openalex.org/W1546411676","https://openalex.org/W1588401315","https://openalex.org/W1676820704","https://openalex.org/W1686810756","https://openalex.org/W1797070008","https://openalex.org/W1806891645","https://openalex.org/W1899249567","https://openalex.org/W1968969471","https://openalex.org/W1988790447","https://openalex.org/W2062118960","https://openalex.org/W2102017903","https://openalex.org/W2110798204","https://openalex.org/W2112796928","https://openalex.org/W2117499988","https://openalex.org/W2117539524","https://openalex.org/W2119821739","https://openalex.org/W2149933564","https://openalex.org/W2155893237","https://openalex.org/W2163605009","https://openalex.org/W2172734211","https://openalex.org/W2244122599","https://openalex.org/W2300867606","https://openalex.org/W2335728318","https://openalex.org/W2533598788","https://openalex.org/W2593807705","https://openalex.org/W2612983688","https://openalex.org/W2912934387","https://openalex.org/W2919115771","https://openalex.org/W2951696358","https://openalex.org/W2962835968","https://openalex.org/W2963446085","https://openalex.org/W2963986115","https://openalex.org/W2990062256","https://openalex.org/W3118608800","https://openalex.org/W4212883601","https://openalex.org/W4239510810","https://openalex.org/W4285719527","https://openalex.org/W4299518610","https://openalex.org/W6632670727","https://openalex.org/W6635310694","https://openalex.org/W6637373629","https://openalex.org/W6638183220","https://openalex.org/W6639736602","https://openalex.org/W6675112735","https://openalex.org/W6676481782","https://openalex.org/W6677604277","https://openalex.org/W6682132143","https://openalex.org/W6684191040","https://openalex.org/W6703116779","https://openalex.org/W6713348437","https://openalex.org/W6734138641","https://openalex.org/W6737496325"],"related_works":["https://openalex.org/W2081982437","https://openalex.org/W4394857231","https://openalex.org/W4377865163","https://openalex.org/W2795259429","https://openalex.org/W3193857078","https://openalex.org/W2888956734","https://openalex.org/W3000197790","https://openalex.org/W4315865067","https://openalex.org/W2979433843","https://openalex.org/W3208304128"],"abstract_inverted_index":{"In":[0],"this":[1,123],"paper,":[2],"we":[3,102],"propose":[4],"a":[5,12,20,26,47,61],"new":[6,62,75],"heuristic":[7],"training":[8,72,100,119,165],"procedure":[9],"to":[10,25,69,151,176],"help":[11],"deep":[13],"neural":[14],"network":[15],"(DNN)":[16],"repeatedly":[17],"escape":[18],"from":[19],"local":[21,28],"minimum":[22],"and":[23,58,113,169],"move":[24],"better":[27,78],"minimum.":[29],"Our":[30],"method":[31,134],"repeats":[32],"the":[33,40,43,52,55,71,74,82,88,117,137,148,153],"following":[34],"processes":[35],"multiple":[36,92],"times:":[37],"randomly":[38,93],"reinitializing":[39],"weights":[41,53],"of":[42,46,54,64,107,147,155],"last":[44],"layer":[45],"converged":[48],"DNN":[49,129],"while":[50],"preserving":[51],"remaining":[56],"layers,":[57],"then":[59],"conducting":[60],"round":[63,76],"training.":[65],"The":[66],"motivation":[67],"is":[68],"make":[70],"in":[73,87,158],"learn":[77],"parameters":[79,85],"based":[80,97],"on":[81,98,127],"\u201cgood\u201d":[83],"initial":[84],"learned":[86],"previous":[89],"round.":[90],"With":[91],"initialized":[94],"DNNs":[95,108,161,171],"trained":[96],"our":[99,133],"procedure,":[101],"can":[103],"obtain":[104],"an":[105],"ensemble":[106,139,156],"that":[109,132],"are":[110,172],"more":[111],"accurate":[112],"diverse":[114],"compared":[115],"with":[116],"normal":[118],"procedure.":[120],"We":[121,142],"call":[122],"framework":[124,150],"\u201cretraining\u201d.":[125],"Experiments":[126],"eight":[128],"models":[130],"show":[131],"generally":[135],"outperforms":[136],"state-of-the-art":[138],"learning":[140,157],"methods.":[141],"also":[143],"provide":[144],"two":[145],"variants":[146],"retraining":[149],"tackle":[152],"tasks":[154],"which":[159],"1)":[160],"exhibit":[162],"very":[163],"high":[164],"accuracies":[166],"(e.g.,":[167],")":[168],"2)":[170],"too":[173],"computationally":[174],"expensive":[175],"train.":[177]},"counts_by_year":[{"year":2025,"cited_by_count":4},{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":4},{"year":2019,"cited_by_count":2}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
