{"id":"https://openalex.org/W2791460829","doi":"https://doi.org/10.1109/access.2018.2796722","title":"Image Classification Based on the Boost Convolutional Neural Network","display_name":"Image Classification Based on the Boost Convolutional Neural Network","publication_year":2018,"publication_date":"2018-01-01","ids":{"openalex":"https://openalex.org/W2791460829","doi":"https://doi.org/10.1109/access.2018.2796722","mag":"2791460829"},"language":"en","primary_location":{"id":"doi:10.1109/access.2018.2796722","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2018.2796722","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.2018.2796722","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5052639662","display_name":"Shin\u2010Jye Lee","orcid":"https://orcid.org/0000-0003-4265-5016"},"institutions":[{"id":"https://openalex.org/I148366613","display_name":"National Yang Ming Chiao Tung University","ror":"https://ror.org/00se2k293","country_code":"TW","type":"education","lineage":["https://openalex.org/I148366613"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Shin-Jye Lee","raw_affiliation_strings":["Institute of Technology Management, National Chiao Tung University, Hsinchu, Taiwan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Technology Management, National Chiao Tung University, Hsinchu, Taiwan","institution_ids":["https://openalex.org/I148366613"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5007638294","display_name":"Tonglin Chen","orcid":"https://orcid.org/0000-0003-2290-5612"},"institutions":[{"id":"https://openalex.org/I189210763","display_name":"Yunnan University","ror":"https://ror.org/0040axw97","country_code":"CN","type":"education","lineage":["https://openalex.org/I189210763"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tonglin Chen","raw_affiliation_strings":["National Pilot School of Software, Yunnan University, Kunming, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Pilot School of Software, Yunnan University, Kunming, China","institution_ids":["https://openalex.org/I189210763"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102224581","display_name":"Lun Yu","orcid":null},"institutions":[{"id":"https://openalex.org/I189210763","display_name":"Yunnan University","ror":"https://ror.org/0040axw97","country_code":"CN","type":"education","lineage":["https://openalex.org/I189210763"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lun Yu","raw_affiliation_strings":["National Pilot School of Software, Yunnan University, Kunming, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Pilot School of Software, Yunnan University, Kunming, China","institution_ids":["https://openalex.org/I189210763"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5037202974","display_name":"Chin\u2010Hui Lai","orcid":"https://orcid.org/0000-0002-7512-2964"},"institutions":[{"id":"https://openalex.org/I151221077","display_name":"Chung Yuan Christian University","ror":"https://ror.org/02w8ws377","country_code":"TW","type":"education","lineage":["https://openalex.org/I151221077"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Chin-Hui Lai","raw_affiliation_strings":["Department of Information Management, Chung Yuan Christian University, Chungli, Taiwan"],"raw_orcid":"https://orcid.org/0000-0002-7512-2964","affiliations":[{"raw_affiliation_string":"Department of Information Management, Chung Yuan Christian University, Chungli, Taiwan","institution_ids":["https://openalex.org/I151221077"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":8.7857,"has_fulltext":false,"cited_by_count":88,"citation_normalized_percentile":{"value":0.98112839,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":100},"biblio":{"volume":"6","issue":null,"first_page":"12755","last_page":"12768"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9987999796867371,"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":0.9987999796867371,"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":0.9958000183105469,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.9954000115394592,"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/softmax-function","display_name":"Softmax function","score":0.9404240250587463},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.869126558303833},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8435768485069275},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7636034488677979},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6206135153770447},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.5844082832336426},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.48315709829330444},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4775325059890747},{"id":"https://openalex.org/keywords/adaboost","display_name":"AdaBoost","score":0.44771331548690796},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.44178682565689087},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.37050095200538635},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.24722665548324585}],"concepts":[{"id":"https://openalex.org/C188441871","wikidata":"https://www.wikidata.org/wiki/Q7554146","display_name":"Softmax function","level":3,"score":0.9404240250587463},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.869126558303833},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8435768485069275},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7636034488677979},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6206135153770447},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.5844082832336426},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.48315709829330444},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4775325059890747},{"id":"https://openalex.org/C141404830","wikidata":"https://www.wikidata.org/wiki/Q2823869","display_name":"AdaBoost","level":3,"score":0.44771331548690796},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.44178682565689087},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.37050095200538635},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.24722665548324585}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2018.2796722","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2018.2796722","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:327021336bbf43cfa30b88b1f954b992","is_oa":true,"landing_page_url":"https://doaj.org/article/327021336bbf43cfa30b88b1f954b992","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 6, Pp 12755-12768 (2018)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2018.2796722","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2018.2796722","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/G1639443436","display_name":null,"funder_award_id":"MOST 106-2410-H-033-013","funder_id":"https://openalex.org/F4320322795","funder_display_name":"Ministry of Science and Technology, Taiwan"},{"id":"https://openalex.org/G2206434784","display_name":"\u6570\u636e\u9a71\u52a8\u7684\u8f6f\u4ef6\u8fc7\u7a0b\u6316\u6398\u7814\u7a76","funder_award_id":"61662085","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6135574011","display_name":"\u9488\u5bf9\u65f6\u95f4\u5e8f\u5217\u805a\u7c7b\u95ee\u9898\u7684\u7279\u5f81\u5b66\u4e60\u4e0e\u96c6\u6210\u5b66\u4e60\u7814\u7a76","funder_award_id":"61663046","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G802297680","display_name":null,"funder_award_id":"61402397","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8830114545","display_name":null,"funder_award_id":"2016FB104","funder_id":"https://openalex.org/F4320332533","funder_display_name":"Applied Basic Research Foundation of Yunnan Province"},{"id":"https://openalex.org/G8997872917","display_name":null,"funder_award_id":"61379032","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/F4320322795","display_name":"Ministry of Science and Technology, Taiwan","ror":"https://ror.org/02kv4zf79"},{"id":"https://openalex.org/F4320332533","display_name":"Applied Basic Research Foundation of Yunnan Province","ror":"https://ror.org/030jhb479"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":25,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W1534477342","https://openalex.org/W1677182931","https://openalex.org/W1836465849","https://openalex.org/W1968969471","https://openalex.org/W1988790447","https://openalex.org/W2037595167","https://openalex.org/W2074772891","https://openalex.org/W2095705004","https://openalex.org/W2100495367","https://openalex.org/W2101926813","https://openalex.org/W2125297759","https://openalex.org/W2127242687","https://openalex.org/W2130325614","https://openalex.org/W2135293965","https://openalex.org/W2153635508","https://openalex.org/W2163605009","https://openalex.org/W2170393096","https://openalex.org/W2911964244","https://openalex.org/W2912934387","https://openalex.org/W4212883601","https://openalex.org/W4248437541","https://openalex.org/W6638667902","https://openalex.org/W6674330103","https://openalex.org/W6684191040"],"related_works":["https://openalex.org/W2899027234","https://openalex.org/W4323060069","https://openalex.org/W4226493464","https://openalex.org/W4312417841","https://openalex.org/W3133861977","https://openalex.org/W2951211570","https://openalex.org/W3103566983","https://openalex.org/W3029198973","https://openalex.org/W2911497689","https://openalex.org/W4229443568"],"abstract_inverted_index":{"Convolutional":[0],"neural":[1,71],"networks":[2],"(CNNs),":[3],"which":[4,42],"are":[5,21,43,53],"composed":[6],"of":[7,15,37,66,78,102,104],"multiple":[8,18],"processing":[9],"layers":[10],"to":[11,45,55,74,87],"learn":[12],"the":[13,22,57,64,76,79,84,89,105,112],"representations":[14],"data":[16],"with":[17],"abstract":[19],"levels,":[20],"most":[23],"successful":[24],"machine":[25],"learning":[26],"models":[27,33],"in":[28,98],"recent":[29],"years.":[30],"However,":[31],"these":[32],"can":[34],"have":[35],"millions":[36],"parameters":[38],"and":[39,47,81,109,116],"many":[40],"layers,":[41],"difficult":[44],"train,":[46],"sometimes":[48],"several":[49],"days":[50],"or":[51],"weeks":[52],"required":[54],"tune":[56],"parameters.":[58],"Within":[59],"this":[60],"paper,":[61],"we":[62],"present":[63],"usage":[65],"a":[67,99],"trained":[68,106],"deep":[69],"convolutional":[70],"network":[72],"model":[73],"extract":[75],"features":[77],"images,":[80],"then,":[82],"used":[83],"AdaBoost":[85],"algorithm":[86],"assemble":[88],"Softmax":[90],"classifiers":[91],"into":[92],"recognizable":[93],"images.":[94],"This":[95],"method":[96],"resulted":[97],"3%":[100],"increase":[101],"accuracy":[103],"CNN":[107],"models,":[108],"dramatically":[110],"reduced":[111],"retraining":[113],"time":[114],"cost,":[115],"thus,":[117],"it":[118],"has":[119],"good":[120],"application":[121],"prospects.":[122]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":8},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":18},{"year":2021,"cited_by_count":15},{"year":2020,"cited_by_count":15},{"year":2019,"cited_by_count":14},{"year":2018,"cited_by_count":8}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
