{"id":"https://openalex.org/W4291155707","doi":"https://doi.org/10.3390/sym14081671","title":"A Deep-Learning Method for the Classification of Apple Varieties via Leaf Images from Different Growth Periods in Natural Environment","display_name":"A Deep-Learning Method for the Classification of Apple Varieties via Leaf Images from Different Growth Periods in Natural Environment","publication_year":2022,"publication_date":"2022-08-11","ids":{"openalex":"https://openalex.org/W4291155707","doi":"https://doi.org/10.3390/sym14081671"},"language":"en","primary_location":{"id":"doi:10.3390/sym14081671","is_oa":true,"landing_page_url":"https://doi.org/10.3390/sym14081671","pdf_url":"https://www.mdpi.com/2073-8994/14/8/1671/pdf?version=1661243811","source":{"id":"https://openalex.org/S190787756","display_name":"Symmetry","issn_l":"2073-8994","issn":["2073-8994"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Symmetry","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/2073-8994/14/8/1671/pdf?version=1661243811","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5028485558","display_name":"Junkang Chen","orcid":"https://orcid.org/0000-0002-0149-7720"},"institutions":[{"id":"https://openalex.org/I16295237","display_name":"Gansu Agricultural University","ror":"https://ror.org/05ym42410","country_code":"CN","type":"education","lineage":["https://openalex.org/I16295237"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Junkang Chen","raw_affiliation_strings":["College of Information Science and Technology, Gansu Agricultural University, No.1, Yinmencun Road, Lanzhou 730070, China"],"raw_orcid":"https://orcid.org/0000-0002-0149-7720","affiliations":[{"raw_affiliation_string":"College of Information Science and Technology, Gansu Agricultural University, No.1, Yinmencun Road, Lanzhou 730070, China","institution_ids":["https://openalex.org/I16295237"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5070354636","display_name":"Junying Han","orcid":"https://orcid.org/0000-0001-9405-279X"},"institutions":[{"id":"https://openalex.org/I16295237","display_name":"Gansu Agricultural University","ror":"https://ror.org/05ym42410","country_code":"CN","type":"education","lineage":["https://openalex.org/I16295237"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Junying Han","raw_affiliation_strings":["College of Information Science and Technology, Gansu Agricultural University, No.1, Yinmencun Road, Lanzhou 730070, China"],"raw_orcid":"https://orcid.org/0000-0001-9405-279X","affiliations":[{"raw_affiliation_string":"College of Information Science and Technology, Gansu Agricultural University, No.1, Yinmencun Road, Lanzhou 730070, China","institution_ids":["https://openalex.org/I16295237"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103233885","display_name":"Chengzhong Liu","orcid":"https://orcid.org/0000-0002-6130-7773"},"institutions":[{"id":"https://openalex.org/I16295237","display_name":"Gansu Agricultural University","ror":"https://ror.org/05ym42410","country_code":"CN","type":"education","lineage":["https://openalex.org/I16295237"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chengzhong Liu","raw_affiliation_strings":["College of Information Science and Technology, Gansu Agricultural University, No.1, Yinmencun Road, Lanzhou 730070, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Information Science and Technology, Gansu Agricultural University, No.1, Yinmencun Road, Lanzhou 730070, China","institution_ids":["https://openalex.org/I16295237"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102010769","display_name":"Yefeng Wang","orcid":"https://orcid.org/0000-0003-2153-8187"},"institutions":[{"id":"https://openalex.org/I16295237","display_name":"Gansu Agricultural University","ror":"https://ror.org/05ym42410","country_code":"CN","type":"education","lineage":["https://openalex.org/I16295237"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yefeng Wang","raw_affiliation_strings":["College of Information Science and Technology, Gansu Agricultural University, No.1, Yinmencun Road, Lanzhou 730070, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Information Science and Technology, Gansu Agricultural University, No.1, Yinmencun Road, Lanzhou 730070, China","institution_ids":["https://openalex.org/I16295237"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5082998387","display_name":"Hangchi Shen","orcid":null},"institutions":[{"id":"https://openalex.org/I16295237","display_name":"Gansu Agricultural University","ror":"https://ror.org/05ym42410","country_code":"CN","type":"education","lineage":["https://openalex.org/I16295237"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hangchi Shen","raw_affiliation_strings":["College of Information Science and Technology, Gansu Agricultural University, No.1, Yinmencun Road, Lanzhou 730070, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Information Science and Technology, Gansu Agricultural University, No.1, Yinmencun Road, Lanzhou 730070, China","institution_ids":["https://openalex.org/I16295237"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100408803","display_name":"Long Li","orcid":"https://orcid.org/0000-0003-2783-8869"},"institutions":[{"id":"https://openalex.org/I16295237","display_name":"Gansu Agricultural University","ror":"https://ror.org/05ym42410","country_code":"CN","type":"education","lineage":["https://openalex.org/I16295237"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Long Li","raw_affiliation_strings":["College of Information Science and Technology, Gansu Agricultural University, No.1, Yinmencun Road, Lanzhou 730070, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Information Science and Technology, Gansu Agricultural University, No.1, Yinmencun Road, Lanzhou 730070, China","institution_ids":["https://openalex.org/I16295237"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5070354636"],"corresponding_institution_ids":["https://openalex.org/I16295237"],"apc_list":{"value":2000,"currency":"CHF","value_usd":2165},"apc_paid":{"value":2000,"currency":"CHF","value_usd":2165},"fwci":5.0393,"has_fulltext":true,"cited_by_count":25,"citation_normalized_percentile":{"value":0.94840718,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":99},"biblio":{"volume":"14","issue":"8","first_page":"1671","last_page":"1671"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10616","display_name":"Smart Agriculture and AI","score":0.9961000084877014,"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":0.9961000084877014,"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":0.9668999910354614,"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"}},{"id":"https://openalex.org/T14365","display_name":"Leaf Properties and Growth Measurement","score":0.960099995136261,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7004877924919128},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5936732292175293},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5540652275085449},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.514886736869812},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.46258020401000977},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.4620814323425293},{"id":"https://openalex.org/keywords/softmax-function","display_name":"Softmax function","score":0.43534865975379944},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3784918785095215},{"id":"https://openalex.org/keywords/biology","display_name":"Biology","score":0.07403445243835449}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7004877924919128},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5936732292175293},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5540652275085449},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.514886736869812},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.46258020401000977},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.4620814323425293},{"id":"https://openalex.org/C188441871","wikidata":"https://www.wikidata.org/wiki/Q7554146","display_name":"Softmax function","level":3,"score":0.43534865975379944},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3784918785095215},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.07403445243835449},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.3390/sym14081671","is_oa":true,"landing_page_url":"https://doi.org/10.3390/sym14081671","pdf_url":"https://www.mdpi.com/2073-8994/14/8/1671/pdf?version=1661243811","source":{"id":"https://openalex.org/S190787756","display_name":"Symmetry","issn_l":"2073-8994","issn":["2073-8994"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Symmetry","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:c2bddaa2707d48ceb13c852f0537d7c9","is_oa":true,"landing_page_url":"https://doaj.org/article/c2bddaa2707d48ceb13c852f0537d7c9","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":"Symmetry, Vol 14, Iss 8, p 1671 (2022)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/2073-8994/14/8/1671/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/sym14081671","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Symmetry; Volume 14; Issue 8; Pages: 1671","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/sym14081671","is_oa":true,"landing_page_url":"https://doi.org/10.3390/sym14081671","pdf_url":"https://www.mdpi.com/2073-8994/14/8/1671/pdf?version=1661243811","source":{"id":"https://openalex.org/S190787756","display_name":"Symmetry","issn_l":"2073-8994","issn":["2073-8994"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Symmetry","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","score":0.6399999856948853,"display_name":"Industry, innovation and infrastructure"}],"awards":[{"id":"https://openalex.org/G6693603692","display_name":null,"funder_award_id":"20JR5RA023","funder_id":"https://openalex.org/F4320322880","funder_display_name":"Natural Science Foundation of Gansu Province"}],"funders":[{"id":"https://openalex.org/F4320322880","display_name":"Natural Science Foundation of Gansu Province","ror":null},{"id":"https://openalex.org/F4320324782","display_name":"Gansu Agricultural University","ror":"https://ror.org/05ym42410"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4291155707.pdf","grobid_xml":"https://content.openalex.org/works/W4291155707.grobid-xml"},"referenced_works_count":18,"referenced_works":["https://openalex.org/W1967587796","https://openalex.org/W2139135476","https://openalex.org/W2163605009","https://openalex.org/W2250488071","https://openalex.org/W2470803522","https://openalex.org/W2752782242","https://openalex.org/W2769149485","https://openalex.org/W2909113739","https://openalex.org/W2970987838","https://openalex.org/W2981969275","https://openalex.org/W2997032006","https://openalex.org/W3003233274","https://openalex.org/W3138516171","https://openalex.org/W3166630474","https://openalex.org/W3183430956","https://openalex.org/W4237752682","https://openalex.org/W6687483927","https://openalex.org/W6757934023"],"related_works":["https://openalex.org/W3107204728","https://openalex.org/W4287591324","https://openalex.org/W3108503355","https://openalex.org/W3090555870","https://openalex.org/W4226420367","https://openalex.org/W2962876041","https://openalex.org/W3022820045","https://openalex.org/W2899027234","https://openalex.org/W2997424368","https://openalex.org/W1996690921"],"abstract_inverted_index":{"With":[0],"the":[1,31,37,43,55,61,67,79,107,131,142,145,147,152,157,170,177,186,199,204,251,255,262,267,279,283,287,317,360],"continuous":[2],"innovation":[3],"and":[4,33,41,94,103,161,181,196,225,239,253,274,278,296,332,343,355],"development":[5,35],"of":[6,11,19,26,36,47,58,69,73,82,125,144,165,173,189,214,229,270,282,286,304,320,341],"technologies":[7],"for":[8,98,116,234,237,241,348],"breeding":[9,44],"varieties":[10,18,28,59,70,219],"fruits,":[12],"there":[13],"are":[14],"more":[15],"than":[16],"8000":[17],"apples":[20],"in":[21,76,101,310,359],"existence.":[22],"The":[23,120,207,243,307],"accurate":[24,187],"identification":[25,57,351],"apple":[27,39,74,117,200,218,321,349],"can":[29],"promote":[30],"healthy":[32],"stable":[34],"global":[38],"industry":[40],"protect":[42],"property":[45],"rights":[46],"rights-holders.":[48],"To":[49],"avoid":[50],"economic":[51],"losses":[52],"due":[53],"to":[54,96,129,135,141,155,168,194],"improper":[56],"at":[60,220],"seedling-procurement":[62],"stage,":[63],"this":[64,311,327],"paper":[65,312],"proposes":[66],"classification":[68,84,114,201,245,256,318],"using":[71],"images":[72,231],"leaves":[75,215],"conjunction":[77],"with":[78,87,261,328],"network":[80],"models":[81],"traditional":[83],"methods,":[85,89],"supplemented":[86],"deep-learning":[88],"such":[90],"as":[91,259],"AlexNet,":[92],"VGG,":[93],"ResNet,":[95],"account":[97],"their":[99],"shortcomings":[100],"robustness":[102],"generalizability.":[104],"We":[105],"used":[106,128,233],"Multi-Attention":[108],"Fusion":[109],"Convolutional":[110],"Neural":[111],"Network":[112],"(MAFNet)":[113],"method":[115,308],"leaf":[118],"images.":[119],"convolutional":[121],"block":[122],"distribution":[123,172],"pattern":[124],"[2,2,2,2]":[126],"is":[127,149],"drive":[130],"feature":[132,158,183],"extraction":[133,159,188],"layer":[134],"have":[136],"a":[137,163,212,329,333,338],"symmetric":[138],"structure.":[139],"According":[140],"characteristics":[143],"dataset,":[146],"model":[148,154],"based":[150],"on":[151,211],"ResNet":[153],"optimize":[156],"module":[160],"integrate":[162],"variety":[164],"attention":[166],"mechanisms":[167],"achieve":[169],"weight":[171],"channel":[174],"features,":[175,191],"reduce":[176],"interference":[178],"information":[179],"before":[180],"after":[182],"extraction,":[184],"complete":[185],"image":[190],"from":[192,216],"low-dimensional":[193],"high-dimensional,":[195],"finally":[197],"obtain":[198],"results":[202],"through":[203],"Softmax":[205],"function.":[206],"experiments":[208],"were":[209,232],"conducted":[210],"mixture":[213],"30":[217],"2":[221],"growth":[222],"stages:":[223],"tender":[224],"mature.":[226],"A":[227],"total":[228],"14,400":[230],"training,":[235],"2400":[236],"validation,":[238],"7200":[240],"testing.":[242],"model\u2019s":[244],"accuracy":[246,252,268,280,302,319],"was":[247],"98.14%,":[248],"which":[249],"improved":[250],"reduced":[254],"imputation":[257],"time":[258],"compared":[260],"previous":[263],"model.":[264],"Among":[265],"them,":[266],"rate":[269,281,303],"\u201cRed":[271,292],"General\u201d,":[272,293],"\u201cSinanoGold\u201d,":[273],"\u201cJonagold\u201d":[275],"reached":[276],"100%,":[277],"bud":[284],"variant":[285],"Fuji":[288],"line":[289],"(\u201cFuji":[290],"2001\u201d,":[291],"\u201cYanfu":[294,297],"0\u201d.":[295],"3\u201d)":[298],"also":[299,325],"had":[300],"an":[301,344],"over":[305],"90%.":[306],"proposed":[309],"not":[313],"only":[314],"significantly":[315],"improves":[316],"cultivars,":[322],"but":[323],"it":[324],"achieves":[326],"low":[330],"cost":[331],"high":[334],"efficiency":[335],"level,":[336],"providing":[337],"new":[339],"way":[340],"thinking":[342],"essential":[345],"technical":[346],"reference":[347],"cultivar":[350],"by":[352],"growers,":[353],"operators,":[354],"law":[356],"enforcement":[357],"supervisors":[358],"production":[361],"practice.":[362]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":12},{"year":2024,"cited_by_count":7},{"year":2023,"cited_by_count":5}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}