{"id":"https://openalex.org/W4408565035","doi":"https://doi.org/10.1109/icdmw65004.2024.00087","title":"Discrimination Of Brown Spot Leaf Disease From RGB Data Of Image","display_name":"Discrimination Of Brown Spot Leaf Disease From RGB Data Of Image","publication_year":2024,"publication_date":"2024-12-09","ids":{"openalex":"https://openalex.org/W4408565035","doi":"https://doi.org/10.1109/icdmw65004.2024.00087"},"language":"en","primary_location":{"id":"doi:10.1109/icdmw65004.2024.00087","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icdmw65004.2024.00087","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Data Mining Workshops (ICDMW)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Nao Yuasa","orcid":null},"institutions":[{"id":"https://openalex.org/I60134161","display_name":"Nagoya University","ror":"https://ror.org/04chrp450","country_code":"JP","type":"education","lineage":["https://openalex.org/I60134161"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Nao Yuasa","raw_affiliation_strings":["Nagoya University,Department of Informatics,Nagoya,Japan"],"affiliations":[{"raw_affiliation_string":"Nagoya University,Department of Informatics,Nagoya,Japan","institution_ids":["https://openalex.org/I60134161"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5116677964","display_name":"Daisuke Minamisawa","orcid":null},"institutions":[{"id":"https://openalex.org/I60134161","display_name":"Nagoya University","ror":"https://ror.org/04chrp450","country_code":"JP","type":"education","lineage":["https://openalex.org/I60134161"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Daisuke Minamisawa","raw_affiliation_strings":["Nagoya University,Department of Informatics,Nagoya,Japan"],"affiliations":[{"raw_affiliation_string":"Nagoya University,Department of Informatics,Nagoya,Japan","institution_ids":["https://openalex.org/I60134161"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5020248302","display_name":"Ayana Takai","orcid":null},"institutions":[{"id":"https://openalex.org/I60134161","display_name":"Nagoya University","ror":"https://ror.org/04chrp450","country_code":"JP","type":"education","lineage":["https://openalex.org/I60134161"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Ayana Takai","raw_affiliation_strings":["Nagoya University,Department of Informatics,Nagoya,Japan"],"affiliations":[{"raw_affiliation_string":"Nagoya University,Department of Informatics,Nagoya,Japan","institution_ids":["https://openalex.org/I60134161"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5116677965","display_name":"Masaya Oirase","orcid":null},"institutions":[{"id":"https://openalex.org/I60134161","display_name":"Nagoya University","ror":"https://ror.org/04chrp450","country_code":"JP","type":"education","lineage":["https://openalex.org/I60134161"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Masaya Oirase","raw_affiliation_strings":["Nagoya University,Department of Informatics,Nagoya,Japan"],"affiliations":[{"raw_affiliation_string":"Nagoya University,Department of Informatics,Nagoya,Japan","institution_ids":["https://openalex.org/I60134161"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5036383728","display_name":"Eisuke Kita","orcid":null},"institutions":[{"id":"https://openalex.org/I60134161","display_name":"Nagoya University","ror":"https://ror.org/04chrp450","country_code":"JP","type":"education","lineage":["https://openalex.org/I60134161"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Eisuke Kita","raw_affiliation_strings":["Nagoya University,Department of Informatics,Nagoya,Japan"],"affiliations":[{"raw_affiliation_string":"Nagoya University,Department of Informatics,Nagoya,Japan","institution_ids":["https://openalex.org/I60134161"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I60134161"],"apc_list":null,"apc_paid":null,"fwci":0.3126,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.62021732,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"626","last_page":"631"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10825","display_name":"Plant Pathogens and Fungal Diseases","score":0.9782999753952026,"subfield":{"id":"https://openalex.org/subfields/1307","display_name":"Cell Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},"topics":[{"id":"https://openalex.org/T10825","display_name":"Plant Pathogens and Fungal Diseases","score":0.9782999753952026,"subfield":{"id":"https://openalex.org/subfields/1307","display_name":"Cell Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T12795","display_name":"Banana Cultivation and Research","score":0.9735999703407288,"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/T10616","display_name":"Smart Agriculture and AI","score":0.965399980545044,"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/rgb-color-model","display_name":"RGB color model","score":0.5609963536262512},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5550692677497864},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5347031354904175},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.48158928751945496},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.42737454175949097},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.35119718313217163}],"concepts":[{"id":"https://openalex.org/C82990744","wikidata":"https://www.wikidata.org/wiki/Q166194","display_name":"RGB color model","level":2,"score":0.5609963536262512},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5550692677497864},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5347031354904175},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.48158928751945496},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.42737454175949097},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.35119718313217163}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icdmw65004.2024.00087","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icdmw65004.2024.00087","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Data Mining Workshops (ICDMW)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","score":0.5299999713897705,"id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":5,"referenced_works":["https://openalex.org/W2295598076","https://openalex.org/W3005417318","https://openalex.org/W4249972823","https://openalex.org/W4399269678","https://openalex.org/W4400762160"],"related_works":["https://openalex.org/W2772917594","https://openalex.org/W2036807459","https://openalex.org/W2058170566","https://openalex.org/W2755342338","https://openalex.org/W2166024367","https://openalex.org/W3116076068","https://openalex.org/W2229312674","https://openalex.org/W2951359407","https://openalex.org/W2079911747","https://openalex.org/W1969923398"],"abstract_inverted_index":{"Brown":[0],"spot":[1,23,117,147],"disease":[2,5,25,118,149],"is":[3,35,66,127],"a":[4,76],"that":[6],"has":[7],"black":[8],"and":[9,57,96],"brown":[10,22,116,146],"spots":[11],"on":[12],"the":[13,18,38,42,45,54,64,69,79,82,115,125,130,138,143,151],"leaves.":[14,46,109,153],"This":[15],"paper":[16],"describes":[17],"discrimination":[19,40,112,144],"algorithm":[20],"of":[21,26,44,51,85,107,119,145,150],"leaf":[24,131,148],"tomato":[27,108,120],"leaves":[28,121],"using":[29],"machine":[30,90],"learning.":[31],"Usually,":[32],"this":[33,48],"problem":[34],"solved":[36],"by":[37],"image":[39,43,52,65,105],"from":[41,63],"In":[47],"study,":[49],"instead":[50],"itself,":[53],"Red,":[55],"Green,":[56],"Blue":[58],"(RGB)":[59],"frequency":[60],"distribution":[61],"obtained":[62,123],"taken":[67],"as":[68],"explanatory":[70,86],"variables.":[71,87],"Three":[72],"algorithms":[73],"are":[74,98,102,122,140],"presented":[75],"according":[77],"to":[78,142],"difference":[80],"in":[81],"calculation":[83],"method":[84],"As":[88],"for":[89,114,129],"learning":[91],"methods,":[92],"Random":[93],"Forest,":[94],"Catboost,":[95],"XGBoost":[97,126],"used.":[99],"The":[100,110],"models":[101,139],"trained":[103],"with":[104,133],"data":[106],"best":[111],"accuracy":[113],"when":[124],"applied":[128,141],"images":[132],"their":[134],"background":[135],"images.":[136],"Finally,":[137],"azalea":[152]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-04-21T08:09:41.155169","created_date":"2025-10-10T00:00:00"}