{"id":"https://openalex.org/W4381734489","doi":"https://doi.org/10.3233/aise230024","title":"Applying Knowledge Distillation on Pre-Trained Model for Early Grapevine Detection","display_name":"Applying Knowledge Distillation on Pre-Trained Model for Early Grapevine Detection","publication_year":2023,"publication_date":"2023-06-22","ids":{"openalex":"https://openalex.org/W4381734489","doi":"https://doi.org/10.3233/aise230024"},"language":"en","primary_location":{"id":"doi:10.3233/aise230024","is_oa":true,"landing_page_url":"http://dx.doi.org/10.3233/aise230024","pdf_url":"https://ebooks.iospress.nl/pdf/doi/10.3233/AISE230024","source":{"id":"https://openalex.org/S4210168452","display_name":"Ambient intelligence and smart environments","issn_l":"1875-4163","issn":["1875-4163","1875-4171"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318577","host_organization_name":"IOS Press","host_organization_lineage":["https://openalex.org/P4310318577"],"host_organization_lineage_names":["IOS Press"],"type":"book series"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Ambient Intelligence and Smart Environments","raw_type":"book-chapter"},"type":"book-chapter","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://ebooks.iospress.nl/pdf/doi/10.3233/AISE230024","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5042387053","display_name":"Lilian Hollard","orcid":null},"institutions":[{"id":"https://openalex.org/I96226040","display_name":"Universit\u00e9 de Reims Champagne-Ardenne","ror":"https://ror.org/03hypw319","country_code":"FR","type":"education","lineage":["https://openalex.org/I96226040"]}],"countries":["FR"],"is_corresponding":true,"raw_author_name":"Lilian Hollard","raw_affiliation_strings":["Universit\u00e9 de Reims Champagne-Ardenne, LICIIS, 51687 Reims Cedex 2, France"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Universit\u00e9 de Reims Champagne-Ardenne, LICIIS, 51687 Reims Cedex 2, France","institution_ids":["https://openalex.org/I96226040"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5000907762","display_name":"Lucas Mohimont","orcid":"https://orcid.org/0000-0001-8006-6656"},"institutions":[{"id":"https://openalex.org/I96226040","display_name":"Universit\u00e9 de Reims Champagne-Ardenne","ror":"https://ror.org/03hypw319","country_code":"FR","type":"education","lineage":["https://openalex.org/I96226040"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Lucas Mohimont","raw_affiliation_strings":["Universit\u00e9 de Reims Champagne-Ardenne, LICIIS, 51687 Reims Cedex 2, France"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Universit\u00e9 de Reims Champagne-Ardenne, LICIIS, 51687 Reims Cedex 2, France","institution_ids":["https://openalex.org/I96226040"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5042387053"],"corresponding_institution_ids":["https://openalex.org/I96226040"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.13948199,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11796","display_name":"Horticultural and Viticultural Research","score":1.0,"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/T11796","display_name":"Horticultural and Viticultural Research","score":1.0,"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/T10750","display_name":"Fermentation and Sensory Analysis","score":0.9865000247955322,"subfield":{"id":"https://openalex.org/subfields/1106","display_name":"Food 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/T12314","display_name":"Nuts composition and effects","score":0.9646999835968018,"subfield":{"id":"https://openalex.org/subfields/2916","display_name":"Nutrition and Dietetics"},"field":{"id":"https://openalex.org/fields/29","display_name":"Nursing"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6441830992698669},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5989792346954346},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5834984183311462},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.5209413766860962},{"id":"https://openalex.org/keywords/automation","display_name":"Automation","score":0.5146216154098511},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.49807286262512207},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.48827481269836426},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4690575897693634},{"id":"https://openalex.org/keywords/wine","display_name":"Wine","score":0.41501346230506897},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.2295227348804474},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1749434471130371}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6441830992698669},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5989792346954346},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5834984183311462},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5209413766860962},{"id":"https://openalex.org/C115901376","wikidata":"https://www.wikidata.org/wiki/Q184199","display_name":"Automation","level":2,"score":0.5146216154098511},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.49807286262512207},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.48827481269836426},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4690575897693634},{"id":"https://openalex.org/C55952523","wikidata":"https://www.wikidata.org/wiki/Q3014419","display_name":"Wine","level":2,"score":0.41501346230506897},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.2295227348804474},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1749434471130371},{"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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0},{"id":"https://openalex.org/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.3233/aise230024","is_oa":true,"landing_page_url":"http://dx.doi.org/10.3233/aise230024","pdf_url":"https://ebooks.iospress.nl/pdf/doi/10.3233/AISE230024","source":{"id":"https://openalex.org/S4210168452","display_name":"Ambient intelligence and smart environments","issn_l":"1875-4163","issn":["1875-4163","1875-4171"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318577","host_organization_name":"IOS Press","host_organization_lineage":["https://openalex.org/P4310318577"],"host_organization_lineage_names":["IOS Press"],"type":"book series"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Ambient Intelligence and Smart Environments","raw_type":"book-chapter"},{"id":"pmh:oai:zenodo.org:10374407","is_oa":true,"landing_page_url":"https://doi.org/10.3233/AISE230024","pdf_url":null,"source":{"id":"https://openalex.org/S4306400562","display_name":"Zenodo (CERN European Organization for Nuclear Research)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I67311998","host_organization_name":"European Organization for Nuclear Research","host_organization_lineage":["https://openalex.org/I67311998"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"EAISA 2023, 2nd Workshop on Edge AI for Smart Agriculture, Flic en Flac, Mauritius, 28 June 2023","raw_type":"info:eu-repo/semantics/conferencePaper"}],"best_oa_location":{"id":"doi:10.3233/aise230024","is_oa":true,"landing_page_url":"http://dx.doi.org/10.3233/aise230024","pdf_url":"https://ebooks.iospress.nl/pdf/doi/10.3233/AISE230024","source":{"id":"https://openalex.org/S4210168452","display_name":"Ambient intelligence and smart environments","issn_l":"1875-4163","issn":["1875-4163","1875-4171"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318577","host_organization_name":"IOS Press","host_organization_lineage":["https://openalex.org/P4310318577"],"host_organization_lineage_names":["IOS Press"],"type":"book series"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Ambient Intelligence and Smart Environments","raw_type":"book-chapter"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/2","display_name":"Zero hunger","score":0.8299999833106995}],"awards":[{"id":"https://openalex.org/G6801139879","display_name":null,"funder_award_id":"101097300","funder_id":"https://openalex.org/F4320320300","funder_display_name":"European Commission"},{"id":"https://openalex.org/G6891322245","display_name":null,"funder_award_id":"101097300","funder_id":"https://openalex.org/F4320319005","funder_display_name":"Key Digital Technologies Joint Undertaking"}],"funders":[{"id":"https://openalex.org/F4320309480","display_name":"Nvidia","ror":"https://ror.org/03jdj4y14"},{"id":"https://openalex.org/F4320319005","display_name":"Key Digital Technologies Joint Undertaking","ror":null},{"id":"https://openalex.org/F4320320300","display_name":"European Commission","ror":"https://ror.org/00k4n6c32"},{"id":"https://openalex.org/F4320329579","display_name":"Universit\u00e9 de Reims Champagne-Ardenne","ror":"https://ror.org/03hypw319"},{"id":"https://openalex.org/F4320334322","display_name":"HORIZON EUROPE Framework Programme","ror":null}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4381734489.pdf","grobid_xml":"https://content.openalex.org/works/W4381734489.grobid-xml"},"referenced_works_count":22,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W1570145364","https://openalex.org/W2036730396","https://openalex.org/W2109934232","https://openalex.org/W2361749505","https://openalex.org/W2407061016","https://openalex.org/W2777515691","https://openalex.org/W2809959615","https://openalex.org/W2943309330","https://openalex.org/W2956274063","https://openalex.org/W2963037989","https://openalex.org/W2966147615","https://openalex.org/W2990812820","https://openalex.org/W3039199168","https://openalex.org/W3175496851","https://openalex.org/W3175579854","https://openalex.org/W3203169630","https://openalex.org/W3210311771","https://openalex.org/W3212279596","https://openalex.org/W4283256989","https://openalex.org/W4292428556","https://openalex.org/W4318621307"],"related_works":["https://openalex.org/W2363759231","https://openalex.org/W4206511643","https://openalex.org/W2379779042","https://openalex.org/W2182302923","https://openalex.org/W3096783867","https://openalex.org/W751089648","https://openalex.org/W2365635624","https://openalex.org/W1896538205","https://openalex.org/W4229036515","https://openalex.org/W4380075502"],"abstract_inverted_index":{"The":[0],"development":[1],"of":[2,19,39,127,170,176,193],"Artificial":[3],"Intelligence":[4],"has":[5,45,150],"raised":[6],"interesting":[7],"opportunities":[8],"for":[9,41,70,131,200],"improved":[10],"automation":[11],"in":[12,80],"smart":[13],"agriculture.":[14],"Smart":[15],"viticulture":[16],"is":[17,85,107],"one":[18],"the":[20,37,95,116,119,124,146],"domains":[21],"that":[22],"can":[23],"benefit":[24],"from":[25,54],"Computer-vision":[26,31],"tasks":[27],"through":[28],"field":[29],"sustainability.":[30],"solutions":[32,189],"present":[33,61],"additional":[34],"constraints":[35],"as":[36],"amount":[38,126],"data":[40,128],"good":[42],"training":[43],"convergence":[44],"to":[46,50,64,108,112,129,138,151,155,180],"be":[47,152],"complex":[48],"enough":[49,154],"cover":[51],"sufficient":[52],"features":[53],"desired":[55],"inputs.":[56],"In":[57],"this":[58],"paper,":[59],"we":[60],"a":[62,66,91,182],"study":[63],"implement":[65],"grapevine":[67],"detection":[68,73,148],"improvement":[69,192],"early":[71],"grapes":[72,147],"and":[74,82,99,123,140,172,198,210],"grape":[75],"yield":[76,88,132],"prediction":[77],"whose":[78],"interest":[79],"Champagne":[81],"wine":[83],"companies":[84],"undeniable.":[86],"Earlier":[87],"predictions":[89],"allow":[90],"better":[92],"market":[93],"assessment,":[94],"harvest":[96],"work\u2019s":[97],"organization":[98],"help":[100],"decision-making":[101],"about":[102],"plant":[103],"management.":[104],"Our":[105],"goal":[106],"carry":[109],"estimations":[110],"5":[111],"6":[113],"weeks":[114],"before":[115],"harvest.":[117],"Furthermore,":[118],"grapevines":[120],"growing":[121],"condition":[122],"large":[125],"process":[130],"estimation":[133],"require":[134],"an":[135,158,191],"embedded":[136,159],"device":[137],"acquire":[139],"compute":[141],"deep":[142,177],"learning":[143,178],"inference.":[144],"Thus,":[145],"model":[149],"lightweight":[153],"run":[156],"on":[157,166,216],"device.":[160],"These":[161],"models":[162,179],"were":[163],"subsequently":[164],"pre-trained":[165],"two":[167],"different":[168],"types":[169],"datasets":[171],"several":[173],"layer":[174],"depth":[175],"propose":[181],"pseudo-labelling":[183],"Teacher-Student":[184],"related":[185],"Knowledge":[186],"Distillation.":[187],"Overall":[188],"proposed":[190],"7.56%,":[194],"6.98,":[195],"8.279%,":[196],"7.934%":[197],"13.63%":[199],"f1":[201],"score,":[202],"precision,":[203],"recall,":[204],"mean":[205,211],"average":[206,212],"precision":[207,213],"at":[208],"50":[209],"50-95":[214],"respectively":[215],"BBCH77":[217],"phenological":[218],"stage.":[219]},"counts_by_year":[],"updated_date":"2026-05-21T09:19:25.381259","created_date":"2025-10-10T00:00:00"}
