{"id":"https://openalex.org/W3127158680","doi":"https://doi.org/10.1007/s00521-021-05715-2","title":"Classification of jujube defects in small data sets based on transfer learning","display_name":"Classification of jujube defects in small data sets based on transfer learning","publication_year":2021,"publication_date":"2021-01-30","ids":{"openalex":"https://openalex.org/W3127158680","doi":"https://doi.org/10.1007/s00521-021-05715-2","mag":"3127158680"},"language":"en","primary_location":{"id":"doi:10.1007/s00521-021-05715-2","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s00521-021-05715-2","pdf_url":"https://link.springer.com/content/pdf/10.1007/s00521-021-05715-2.pdf","source":{"id":"https://openalex.org/S147897268","display_name":"Neural Computing and Applications","issn_l":"0941-0643","issn":["0941-0643","1433-3058"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Neural Computing and Applications","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://link.springer.com/content/pdf/10.1007/s00521-021-05715-2.pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5066387292","display_name":"Jianping Ju","orcid":"https://orcid.org/0000-0002-6207-2355"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]},{"id":"https://openalex.org/I4210111616","display_name":"Wuhan Business University","ror":"https://ror.org/0282ggx30","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210111616"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jianping Ju","raw_affiliation_strings":["School of Artificial Intelligence, Hubei Business College, Hubei, 430000, China","School of Electronic Information, Wuhan University, Hubei, 430072, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, Hubei Business College, Hubei, 430000, China","institution_ids":["https://openalex.org/I4210111616"]},{"raw_affiliation_string":"School of Electronic Information, Wuhan University, Hubei, 430072, China","institution_ids":["https://openalex.org/I37461747"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101544973","display_name":"Hong Zheng","orcid":"https://orcid.org/0000-0001-8572-4347"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Hong Zheng","raw_affiliation_strings":["School of Electronic Information, Wuhan University, Hubei, 430072, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electronic Information, Wuhan University, Hubei, 430072, China","institution_ids":["https://openalex.org/I37461747"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5005130995","display_name":"Xiaohang Xu","orcid":"https://orcid.org/0000-0002-0231-3102"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaohang Xu","raw_affiliation_strings":["School of Electronic Information, Wuhan University, Hubei, 430072, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electronic Information, Wuhan University, Hubei, 430072, China","institution_ids":["https://openalex.org/I37461747"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5056275495","display_name":"Zhongyuan Guo","orcid":"https://orcid.org/0000-0002-5445-1400"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhongyuan Guo","raw_affiliation_strings":["School of Electronic Information, Wuhan University, Hubei, 430072, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electronic Information, Wuhan University, Hubei, 430072, China","institution_ids":["https://openalex.org/I37461747"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5050012027","display_name":"Zhaohui Zheng","orcid":"https://orcid.org/0000-0002-7303-4856"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]},{"id":"https://openalex.org/I4210162404","display_name":"China Railway Construction Machinery Research & Design Institute","ror":"https://ror.org/05qw55b97","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210162404"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhaohui Zheng","raw_affiliation_strings":["Department of Public Courses, Wuhan Railway Vocational College of Technology, Hubei, 430205, China","School of Electronic Information, Wuhan University, Hubei, 430072, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Public Courses, Wuhan Railway Vocational College of Technology, Hubei, 430205, China","institution_ids":["https://openalex.org/I4210162404"]},{"raw_affiliation_string":"School of Electronic Information, Wuhan University, Hubei, 430072, China","institution_ids":["https://openalex.org/I37461747"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100308143","display_name":"Mingyu Lin","orcid":null},"institutions":[{"id":"https://openalex.org/I4210111616","display_name":"Wuhan Business University","ror":"https://ror.org/0282ggx30","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210111616"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Mingyu Lin","raw_affiliation_strings":["School of Artificial Intelligence, Hubei Business College, Hubei, 430000, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, Hubei Business College, Hubei, 430000, China","institution_ids":["https://openalex.org/I4210111616"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5101544973"],"corresponding_institution_ids":["https://openalex.org/I37461747"],"apc_list":{"value":2390,"currency":"EUR","value_usd":2990},"apc_paid":{"value":2390,"currency":"EUR","value_usd":2990},"fwci":2.9199,"has_fulltext":true,"cited_by_count":35,"citation_normalized_percentile":{"value":0.9112156,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"34","issue":"5","first_page":"3385","last_page":"3398"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13890","display_name":"Remote Sensing and Land Use","score":0.9883999824523926,"subfield":{"id":"https://openalex.org/subfields/1902","display_name":"Atmospheric Science"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T13890","display_name":"Remote Sensing and Land Use","score":0.9883999824523926,"subfield":{"id":"https://openalex.org/subfields/1902","display_name":"Atmospheric Science"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10616","display_name":"Smart Agriculture and AI","score":0.9850000143051147,"subfield":{"id":"https://openalex.org/subfields/1110","display_name":"Plant Science"},"field":{"id":"https://openalex.org/fields/11","display_name":"Agricultural and Biological Sciences"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10640","display_name":"Spectroscopy and Chemometric Analyses","score":0.9782999753952026,"subfield":{"id":"https://openalex.org/subfields/1602","display_name":"Analytical Chemistry"},"field":{"id":"https://openalex.org/fields/16","display_name":"Chemistry"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/softmax-function","display_name":"Softmax function","score":0.8525837063789368},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6958119869232178},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6554221510887146},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6334842443466187},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5979490876197815},{"id":"https://openalex.org/keywords/transfer-of-learning","display_name":"Transfer of learning","score":0.57421875},{"id":"https://openalex.org/keywords/sorting","display_name":"Sorting","score":0.5334197878837585},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5232657194137573},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.44287461042404175},{"id":"https://openalex.org/keywords/data-set","display_name":"Data set","score":0.43165791034698486},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4183216392993927},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.41793879866600037},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3468497693538666},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3436630368232727},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.11289641261100769}],"concepts":[{"id":"https://openalex.org/C188441871","wikidata":"https://www.wikidata.org/wiki/Q7554146","display_name":"Softmax function","level":3,"score":0.8525837063789368},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6958119869232178},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6554221510887146},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6334842443466187},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5979490876197815},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.57421875},{"id":"https://openalex.org/C111696304","wikidata":"https://www.wikidata.org/wiki/Q2303697","display_name":"Sorting","level":2,"score":0.5334197878837585},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5232657194137573},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.44287461042404175},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.43165791034698486},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4183216392993927},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.41793879866600037},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3468497693538666},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3436630368232727},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.11289641261100769},{"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":1,"locations":[{"id":"doi:10.1007/s00521-021-05715-2","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s00521-021-05715-2","pdf_url":"https://link.springer.com/content/pdf/10.1007/s00521-021-05715-2.pdf","source":{"id":"https://openalex.org/S147897268","display_name":"Neural Computing and Applications","issn_l":"0941-0643","issn":["0941-0643","1433-3058"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Neural Computing and Applications","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1007/s00521-021-05715-2","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s00521-021-05715-2","pdf_url":"https://link.springer.com/content/pdf/10.1007/s00521-021-05715-2.pdf","source":{"id":"https://openalex.org/S147897268","display_name":"Neural Computing and Applications","issn_l":"0941-0643","issn":["0941-0643","1433-3058"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Neural Computing and Applications","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/2","display_name":"Zero hunger","score":0.7300000190734863}],"awards":[{"id":"https://openalex.org/G6716368812","display_name":"\u9ad8\u9891\u65e0\u7ebf\u7535\u6d77\u6d0b\u56de\u6ce2\u5fae\u591a\u666e\u52d2\u6548\u5e94\u7684\u53d1\u73b0\u53ca\u5176\u673a\u7406\u7814\u7a76","funder_award_id":"61771352","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"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3127158680.pdf","grobid_xml":"https://content.openalex.org/works/W3127158680.grobid-xml"},"referenced_works_count":33,"referenced_works":["https://openalex.org/W1916279783","https://openalex.org/W2006422771","https://openalex.org/W2026978702","https://openalex.org/W2029316659","https://openalex.org/W2042566737","https://openalex.org/W2071546401","https://openalex.org/W2096733369","https://openalex.org/W2105106782","https://openalex.org/W2194775991","https://openalex.org/W2211589372","https://openalex.org/W2295107390","https://openalex.org/W2330986406","https://openalex.org/W2473156356","https://openalex.org/W2511933885","https://openalex.org/W2520774990","https://openalex.org/W2594407953","https://openalex.org/W2605439166","https://openalex.org/W2608353599","https://openalex.org/W2759712264","https://openalex.org/W2770376780","https://openalex.org/W2789571202","https://openalex.org/W2804471513","https://openalex.org/W2894104353","https://openalex.org/W2901363261","https://openalex.org/W2907551576","https://openalex.org/W2962858109","https://openalex.org/W2963420686","https://openalex.org/W2963744743","https://openalex.org/W3022086662","https://openalex.org/W3099206234","https://openalex.org/W3104682621","https://openalex.org/W3106411919","https://openalex.org/W6601939488"],"related_works":["https://openalex.org/W3107204728","https://openalex.org/W4287591324","https://openalex.org/W4226420367","https://openalex.org/W2980176872","https://openalex.org/W2962876041","https://openalex.org/W3131922633","https://openalex.org/W2947839263","https://openalex.org/W3120400911","https://openalex.org/W4381430104","https://openalex.org/W2979740303"],"abstract_inverted_index":{"Abstract":[0],"Although":[1],"convolutional":[2,94],"neural":[3,95],"networks":[4],"have":[5],"achieved":[6],"success":[7],"in":[8,18,88,292],"the":[9,19,42,46,51,54,58,61,64,70,76,104,112,117,126,150,155,160,166,171,176,187,194,197,202,206,211,217,224,227,231,236,247,257,265,269,278],"field":[10,20],"of":[11,21,35,53,60,67,78,107,135,138,196,205,226,235,249,273],"image":[12,178],"classification,":[13],"there":[14],"are":[15,242],"still":[16],"challenges":[17],"agricultural":[22],"product":[23],"quality":[24],"sorting":[25,86,120],"such":[26],"as":[27],"machine":[28],"vision-based":[29],"jujube":[30,36,55,85,108,119,139,188,207,218,237,274],"defects":[31,109,189,208,219],"detection.":[32,110],"The":[33,141,239,260,283],"performance":[34],"defect":[37,275],"detection":[38,232],"mainly":[39],"depends":[40],"on":[41,93,175,186],"feature":[43],"extraction":[44],"and":[45,57,97,125,153,159,210,229,233,252,277,288],"classifier":[47],"used.":[48],"Due":[49],"to":[50,74,102,130,164,183,216,222],"diversity":[52],"materials":[56],"variability":[59],"testing":[62],"environment,":[63],"traditional":[65],"method":[66],"manually":[68],"extracting":[69],"features":[71],"often":[72],"fails":[73],"meet":[75,103],"requirements":[77],"practical":[79],"application.":[80],"In":[81],"this":[82],"paper,":[83],"a":[84,132],"model":[87,144,174,199,228,267,284],"small":[89],"data":[90,127,133,179,190,220],"sets":[91],"based":[92],"network":[96],"transfer":[98,225],"learning":[99],"is":[100,145],"proposed":[101],"actual":[105,118],"demand":[106],"Firstly,":[111],"original":[113,142],"images":[114],"collected":[115],"from":[116],"production":[121],"line":[122],"were":[123,128],"pre-processed,":[124],"augmented":[129],"establish":[131],"set":[134,180,221],"five":[136],"categories":[137],"defects.":[140,238],"CNN":[143],"then":[146],"improved":[147],"by":[148,244],"embedding":[149],"SE":[151],"module":[152],"using":[154],"triplet":[156],"loss":[157,162,168],"function":[158,163],"center":[161],"replace":[165],"softmax":[167],"function.":[169],"Finally,":[170],"depth":[172],"pre-training":[173,198],"ImageNet":[177],"was":[181,214],"used":[182],"conduct":[184],"training":[185],"set,":[191],"so":[192],"that":[193,264],"parameters":[195],"could":[200],"fit":[201],"parameter":[203,212],"distribution":[204,213],"image,":[209],"transferred":[215],"complete":[223],"realize":[230],"classification":[234,240,250,271],"results":[241,262],"visualized":[243],"heatmap":[245],"through":[246],"analysis":[248],"accuracy":[251,280,291],"confusion":[253],"matrix":[254],"compared":[255],"with":[256],"comparison":[258],"models.":[259],"experimental":[261],"show":[263],"SE-ResNet50-CL":[266],"optimizes":[268],"fine-grained":[270],"problem":[272],"recognition,":[276],"test":[279],"reaches":[281],"94.15%.":[282],"has":[285],"good":[286],"stability":[287],"high":[289],"recognition":[290],"complex":[293],"environments.":[294]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":11},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":7},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":1}],"updated_date":"2026-06-19T15:47:20.252518","created_date":"2025-10-10T00:00:00"}