{"id":"https://openalex.org/W3183929004","doi":"https://doi.org/10.1109/access.2021.3097050","title":"Grape Leaf Spot Identification Under Limited Samples by Fine Grained-GAN","display_name":"Grape Leaf Spot Identification Under Limited Samples by Fine Grained-GAN","publication_year":2021,"publication_date":"2021-01-01","ids":{"openalex":"https://openalex.org/W3183929004","doi":"https://doi.org/10.1109/access.2021.3097050","mag":"3183929004"},"language":"en","primary_location":{"id":"doi:10.1109/access.2021.3097050","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2021.3097050","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/9312710/09483889.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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","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/ielx7/6287639/9312710/09483889.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5017379162","display_name":"Changjian Zhou","orcid":"https://orcid.org/0000-0002-2094-6405"},"institutions":[{"id":"https://openalex.org/I169572211","display_name":"Northeast Agricultural University","ror":"https://ror.org/0515nd386","country_code":"CN","type":"education","lineage":["https://openalex.org/I169572211"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Changjian Zhou","raw_affiliation_strings":["Department of Modern Educational Technology, Northeast Agricultural University, Harbin, China","Key Laboratory of Agricultural Microbiology of Heilongjiang Province, Northeast Agricultural University, Harbin, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Modern Educational Technology, Northeast Agricultural University, Harbin, China","institution_ids":["https://openalex.org/I169572211"]},{"raw_affiliation_string":"Key Laboratory of Agricultural Microbiology of Heilongjiang Province, Northeast Agricultural University, Harbin, China","institution_ids":["https://openalex.org/I169572211"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101545475","display_name":"Zhiyao Zhang","orcid":"https://orcid.org/0000-0002-2705-6608"},"institutions":[{"id":"https://openalex.org/I169572211","display_name":"Northeast Agricultural University","ror":"https://ror.org/0515nd386","country_code":"CN","type":"education","lineage":["https://openalex.org/I169572211"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhiyao Zhang","raw_affiliation_strings":["College of Electrical and Information, Northeast Agricultural University, Harbin, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Electrical and Information, Northeast Agricultural University, Harbin, China","institution_ids":["https://openalex.org/I169572211"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5061905512","display_name":"Sihan Zhou","orcid":"https://orcid.org/0000-0002-9415-7783"},"institutions":[{"id":"https://openalex.org/I169572211","display_name":"Northeast Agricultural University","ror":"https://ror.org/0515nd386","country_code":"CN","type":"education","lineage":["https://openalex.org/I169572211"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Sihan Zhou","raw_affiliation_strings":["College of Electrical and Information, Northeast Agricultural University, Harbin, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Electrical and Information, Northeast Agricultural University, Harbin, China","institution_ids":["https://openalex.org/I169572211"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5005733530","display_name":"Jinge Xing","orcid":"https://orcid.org/0000-0001-8934-427X"},"institutions":[{"id":"https://openalex.org/I169572211","display_name":"Northeast Agricultural University","ror":"https://ror.org/0515nd386","country_code":"CN","type":"education","lineage":["https://openalex.org/I169572211"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jinge Xing","raw_affiliation_strings":["Department of Modern Educational Technology, Northeast Agricultural University, Harbin, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Modern Educational Technology, Northeast Agricultural University, Harbin, China","institution_ids":["https://openalex.org/I169572211"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5019211546","display_name":"Qiufeng Wu","orcid":"https://orcid.org/0000-0002-4787-2549"},"institutions":[{"id":"https://openalex.org/I169572211","display_name":"Northeast Agricultural University","ror":"https://ror.org/0515nd386","country_code":"CN","type":"education","lineage":["https://openalex.org/I169572211"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qiufeng Wu","raw_affiliation_strings":["College of Arts and Science, Northeast Agricultural University, Harbin, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Arts and Science, Northeast Agricultural University, Harbin, China","institution_ids":["https://openalex.org/I169572211"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5033366428","display_name":"Jia Song","orcid":"https://orcid.org/0000-0002-4019-970X"},"institutions":[{"id":"https://openalex.org/I169572211","display_name":"Northeast Agricultural University","ror":"https://ror.org/0515nd386","country_code":"CN","type":"education","lineage":["https://openalex.org/I169572211"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jia Song","raw_affiliation_strings":["Key Laboratory of Agricultural Microbiology of Heilongjiang Province, Northeast Agricultural University, Harbin, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Key Laboratory of Agricultural Microbiology of Heilongjiang Province, Northeast Agricultural University, Harbin, China","institution_ids":["https://openalex.org/I169572211"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5017379162"],"corresponding_institution_ids":["https://openalex.org/I169572211"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":12.6147,"has_fulltext":true,"cited_by_count":75,"citation_normalized_percentile":{"value":0.98773811,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":100},"biblio":{"volume":"9","issue":null,"first_page":"100480","last_page":"100489"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10616","display_name":"Smart Agriculture and AI","score":0.9994999766349792,"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"}},"topics":[{"id":"https://openalex.org/T10616","display_name":"Smart Agriculture and AI","score":0.9994999766349792,"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/T14365","display_name":"Leaf Properties and Growth Measurement","score":0.9731000065803528,"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/T10111","display_name":"Remote Sensing in Agriculture","score":0.9675999879837036,"subfield":{"id":"https://openalex.org/subfields/2303","display_name":"Ecology"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.7374873161315918},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7269805669784546},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7027231454849243},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.6195683479309082},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.5277348756790161},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.49920654296875},{"id":"https://openalex.org/keywords/hot-spot","display_name":"Hot spot (computer programming)","score":0.47542646527290344},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.4679946303367615},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.4492477476596832},{"id":"https://openalex.org/keywords/detector","display_name":"Detector","score":0.41356411576271057},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.17054536938667297}],"concepts":[{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.7374873161315918},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7269805669784546},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7027231454849243},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6195683479309082},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.5277348756790161},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.49920654296875},{"id":"https://openalex.org/C199672914","wikidata":"https://www.wikidata.org/wiki/Q4241353","display_name":"Hot spot (computer programming)","level":2,"score":0.47542646527290344},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.4679946303367615},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.4492477476596832},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.41356411576271057},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.17054536938667297},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2021.3097050","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2021.3097050","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/9312710/09483889.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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:2bede13506884813a7653f41c18eb509","is_oa":true,"landing_page_url":"https://doaj.org/article/2bede13506884813a7653f41c18eb509","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 9, Pp 100480-100489 (2021)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2021.3097050","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2021.3097050","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/9312710/09483889.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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320325186","display_name":"Northeast Agricultural University","ror":"https://ror.org/0515nd386"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3183929004.pdf","grobid_xml":"https://content.openalex.org/works/W3183929004.grobid-xml"},"referenced_works_count":51,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W1686810756","https://openalex.org/W2099471712","https://openalex.org/W2147764098","https://openalex.org/W2163605009","https://openalex.org/W2173520492","https://openalex.org/W2194775991","https://openalex.org/W2546179086","https://openalex.org/W2592101326","https://openalex.org/W2613718673","https://openalex.org/W2792362452","https://openalex.org/W2904211956","https://openalex.org/W2907194960","https://openalex.org/W2908795719","https://openalex.org/W2945751394","https://openalex.org/W2962879692","https://openalex.org/W2963073614","https://openalex.org/W2963226019","https://openalex.org/W2963426391","https://openalex.org/W2963684088","https://openalex.org/W2971403154","https://openalex.org/W2980069994","https://openalex.org/W2980268141","https://openalex.org/W2988980823","https://openalex.org/W2997809778","https://openalex.org/W3005680136","https://openalex.org/W3006175081","https://openalex.org/W3006264505","https://openalex.org/W3017865550","https://openalex.org/W3033097971","https://openalex.org/W3033864984","https://openalex.org/W3060850527","https://openalex.org/W3107829143","https://openalex.org/W3111506096","https://openalex.org/W3119339683","https://openalex.org/W3132328762","https://openalex.org/W3135587110","https://openalex.org/W3158994220","https://openalex.org/W3159207671","https://openalex.org/W3171062249","https://openalex.org/W4295521014","https://openalex.org/W4320013936","https://openalex.org/W6637373629","https://openalex.org/W6684191040","https://openalex.org/W6685352114","https://openalex.org/W6718140377","https://openalex.org/W6734373134","https://openalex.org/W6735913928","https://openalex.org/W6786702225","https://openalex.org/W6794374880","https://openalex.org/W6794581531"],"related_works":["https://openalex.org/W2379142291","https://openalex.org/W4304092003","https://openalex.org/W2252731128","https://openalex.org/W2360245112","https://openalex.org/W2056851929","https://openalex.org/W2369166484","https://openalex.org/W2736580264","https://openalex.org/W1996708040","https://openalex.org/W2366906938","https://openalex.org/W3000197790"],"abstract_inverted_index":{"In":[0],"practice,":[1,44],"early":[2,20,28],"detection":[3],"of":[4,7,22,30,112,124,244],"disease":[5,31,36],"is":[6,243],"high":[8],"importance":[9],"to":[10,87,106],"practical":[11,246],"value,":[12],"corresponding":[13],"measures":[14],"can":[15,117],"be":[16],"taken":[17],"at":[18],"the":[19,27,57,88,109,113,120,125,139,178,191,196,208],"stage":[21,29],"plant":[23],"disease.":[24],"However,":[25],"in":[26,43,159,168],"or":[32,251],"when":[33],"a":[34,69],"rare":[35,249],"occurs,":[37],"there":[38],"are":[39],"limited":[40,252],"training":[41,63,105,187,253],"samples":[42],"which":[45,94,116,228],"makes":[46],"machine":[47],"learning":[48,51,102,193,220],"especially":[49,222],"deep":[50,101,192,219],"models":[52,103],"hardly":[53],"work":[54],"well":[55],"while":[56,195],"stronger":[58],"representative":[59],"ability":[60,111],"needs":[61],"large-scale":[62],"data.":[64],"To":[65],"solve":[66],"this":[67,160],"problem,":[68],"fine":[70,141,169],"grained-GAN":[71,142,170],"based":[72],"grape":[73,130],"leaf":[74,131],"spot":[75,82,91,132,145,151,173],"identification":[76,214],"method":[77,210],"was":[78,166],"proposed":[79,140,209],"for":[80,104,143,202,248],"local":[81,90,144,150,172],"area":[83,92,146,152,174],"image":[84],"data":[85,147,188,234],"augmentation":[86,235],"generated":[89,158,182],"images":[93,133,154],"were":[95,136,157,184,200],"added":[96],"and":[97,122,181,237],"fed":[98,137],"them":[99],"into":[100,138,190],"further":[107],"strengthen":[108],"generalization":[110],"classification":[114],"models,":[115,194],"effectively":[118],"improve":[119],"accuracy":[121,215],"robustness":[123],"prediction.":[126],"Including":[127],"500":[128],"early-stage":[129],"every":[134,155],"category":[135,156],"augmentation,":[148],"1000":[149],"sub":[153],"study.":[161],"The":[162],"improved":[163],"faster":[164],"R-CNN":[165],"integrated":[167],"as":[171,186],"detector.":[175],"After":[176],"that,":[177],"segmented":[179,198],"sub-images":[180,183,199],"mixed":[185],"input":[189],"original":[197],"used":[201],"testing.":[203],"Experimental":[204],"results":[205],"showed":[206],"that":[207],"had":[211,224],"achieved":[212],"higher":[213],"on":[216],"five":[217],"state-of-art":[218],"models;":[221],"ResNet-50":[223],"got":[225],"96.27%":[226],"accuracy,":[227],"obtained":[229],"significant":[230],"improvements":[231],"than":[232],"other":[233],"methods":[236],"verified":[238],"its":[239],"satisfactory":[240],"performance.":[241],"This":[242],"great":[245],"significance":[247],"diseases":[250],"samples.":[254]},"counts_by_year":[{"year":2025,"cited_by_count":18},{"year":2024,"cited_by_count":19},{"year":2023,"cited_by_count":27},{"year":2022,"cited_by_count":10},{"year":2021,"cited_by_count":1}],"updated_date":"2026-05-06T08:25:59.206177","created_date":"2025-10-10T00:00:00"}