{"id":"https://openalex.org/W4220812717","doi":"https://doi.org/10.1109/sii52469.2022.9708815","title":"Weed and Crop Detection by Combining Crop Row Detection and K-means Clustering in Weed Infested Agricultural Fields","display_name":"Weed and Crop Detection by Combining Crop Row Detection and K-means Clustering in Weed Infested Agricultural Fields","publication_year":2022,"publication_date":"2022-01-09","ids":{"openalex":"https://openalex.org/W4220812717","doi":"https://doi.org/10.1109/sii52469.2022.9708815"},"language":"en","primary_location":{"id":"doi:10.1109/sii52469.2022.9708815","is_oa":false,"landing_page_url":"https://doi.org/10.1109/sii52469.2022.9708815","pdf_url":null,"source":{"id":"https://openalex.org/S4363605592","display_name":"2022 IEEE/SICE International Symposium on System Integration (SII)","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE/SICE International Symposium on System Integration (SII)","raw_type":"proceedings-article"},"type":"conference-paper","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":"https://openalex.org/A5025752000","display_name":"Kumpei Ota","orcid":null},"institutions":[{"id":"https://openalex.org/I1323638106","display_name":"National Agriculture and Food Research Organization","ror":"https://ror.org/023v4bd62","country_code":"JP","type":"government","lineage":["https://openalex.org/I1323638106"]},{"id":"https://openalex.org/I4210143765","display_name":"Institute of Agricultural Machinery","ror":"https://ror.org/03d0gny34","country_code":"JP","type":"facility","lineage":["https://openalex.org/I1323638106","https://openalex.org/I4210143765"]},{"id":"https://openalex.org/I74801974","display_name":"The University of Tokyo","ror":"https://ror.org/057zh3y96","country_code":"JP","type":"education","lineage":["https://openalex.org/I74801974"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Kumpei Ota","raw_affiliation_strings":["The University of Tokyo,Department of Precision Engineering,Tokyo,Japan,113-8656","Institute of Agricultural Machinery, National Agriculture and Food Research Organization, Saitama, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The University of Tokyo,Department of Precision Engineering,Tokyo,Japan,113-8656","institution_ids":["https://openalex.org/I74801974"]},{"raw_affiliation_string":"Institute of Agricultural Machinery, National Agriculture and Food Research Organization, Saitama, Japan","institution_ids":["https://openalex.org/I1323638106","https://openalex.org/I4210143765"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5051800939","display_name":"Jun Younes Louhi Kasahara","orcid":"https://orcid.org/0000-0002-5924-8858"},"institutions":[{"id":"https://openalex.org/I74801974","display_name":"The University of Tokyo","ror":"https://ror.org/057zh3y96","country_code":"JP","type":"education","lineage":["https://openalex.org/I74801974"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Jun Younes Louhi Kasahara","raw_affiliation_strings":["The University of Tokyo,Department of Precision Engineering,Tokyo,Japan,113-8656"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The University of Tokyo,Department of Precision Engineering,Tokyo,Japan,113-8656","institution_ids":["https://openalex.org/I74801974"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5021260328","display_name":"Atsushi Yamashita","orcid":"https://orcid.org/0000-0003-1280-069X"},"institutions":[{"id":"https://openalex.org/I74801974","display_name":"The University of Tokyo","ror":"https://ror.org/057zh3y96","country_code":"JP","type":"education","lineage":["https://openalex.org/I74801974"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Atsushi Yamashita","raw_affiliation_strings":["The University of Tokyo,Department of Precision Engineering,Tokyo,Japan,113-8656"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The University of Tokyo,Department of Precision Engineering,Tokyo,Japan,113-8656","institution_ids":["https://openalex.org/I74801974"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5064103302","display_name":"Hajime Asama","orcid":"https://orcid.org/0000-0002-9482-497X"},"institutions":[{"id":"https://openalex.org/I74801974","display_name":"The University of Tokyo","ror":"https://ror.org/057zh3y96","country_code":"JP","type":"education","lineage":["https://openalex.org/I74801974"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Hajime Asama","raw_affiliation_strings":["The University of Tokyo,Department of Precision Engineering,Tokyo,Japan,113-8656"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The University of Tokyo,Department of Precision Engineering,Tokyo,Japan,113-8656","institution_ids":["https://openalex.org/I74801974"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":16,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"985","last_page":"990"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10616","display_name":"Smart Agriculture and AI","score":0.9993000030517578,"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":0.9993000030517578,"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":0.9642000198364258,"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"}},{"id":"https://openalex.org/T14365","display_name":"Leaf Properties and Growth Measurement","score":0.9564999938011169,"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/weed","display_name":"Weed","score":0.8561131954193115},{"id":"https://openalex.org/keywords/crop","display_name":"Crop","score":0.7703983783721924},{"id":"https://openalex.org/keywords/agronomy","display_name":"Agronomy","score":0.5058245658874512},{"id":"https://openalex.org/keywords/weed-control","display_name":"Weed control","score":0.4683270752429962},{"id":"https://openalex.org/keywords/row-crop","display_name":"Row crop","score":0.4560607969760895},{"id":"https://openalex.org/keywords/crop-yield","display_name":"Crop yield","score":0.4338456094264984},{"id":"https://openalex.org/keywords/agriculture","display_name":"Agriculture","score":0.4092012047767639},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3581695556640625},{"id":"https://openalex.org/keywords/biology","display_name":"Biology","score":0.16860505938529968}],"concepts":[{"id":"https://openalex.org/C2775891814","wikidata":"https://www.wikidata.org/wiki/Q101879","display_name":"Weed","level":2,"score":0.8561131954193115},{"id":"https://openalex.org/C137580998","wikidata":"https://www.wikidata.org/wiki/Q235352","display_name":"Crop","level":2,"score":0.7703983783721924},{"id":"https://openalex.org/C6557445","wikidata":"https://www.wikidata.org/wiki/Q173113","display_name":"Agronomy","level":1,"score":0.5058245658874512},{"id":"https://openalex.org/C147273371","wikidata":"https://www.wikidata.org/wiki/Q2739141","display_name":"Weed control","level":2,"score":0.4683270752429962},{"id":"https://openalex.org/C2776366211","wikidata":"https://www.wikidata.org/wiki/Q17052671","display_name":"Row crop","level":3,"score":0.4560607969760895},{"id":"https://openalex.org/C126343540","wikidata":"https://www.wikidata.org/wiki/Q889514","display_name":"Crop yield","level":2,"score":0.4338456094264984},{"id":"https://openalex.org/C118518473","wikidata":"https://www.wikidata.org/wiki/Q11451","display_name":"Agriculture","level":2,"score":0.4092012047767639},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3581695556640625},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.16860505938529968},{"id":"https://openalex.org/C18903297","wikidata":"https://www.wikidata.org/wiki/Q7150","display_name":"Ecology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/sii52469.2022.9708815","is_oa":false,"landing_page_url":"https://doi.org/10.1109/sii52469.2022.9708815","pdf_url":null,"source":{"id":"https://openalex.org/S4363605592","display_name":"2022 IEEE/SICE International Symposium on System Integration (SII)","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE/SICE International Symposium on System Integration (SII)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6899999976158142,"id":"https://metadata.un.org/sdg/2","display_name":"Zero hunger"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":6,"referenced_works":["https://openalex.org/W1557569703","https://openalex.org/W2133059825","https://openalex.org/W2145023731","https://openalex.org/W2418106930","https://openalex.org/W2803969185","https://openalex.org/W2898498213"],"related_works":["https://openalex.org/W2019082283","https://openalex.org/W2506386864","https://openalex.org/W3049256127","https://openalex.org/W2076074519","https://openalex.org/W2096287037","https://openalex.org/W2178732327","https://openalex.org/W1592917383","https://openalex.org/W2279742145","https://openalex.org/W1966322886","https://openalex.org/W2043829150"],"abstract_inverted_index":{"Crop":[0],"and":[1,14,21,86,109],"weed":[2,22,87],"detection":[3,23,49,88,105],"is":[4,44,50],"an":[5],"essential":[6],"technique":[7],"for":[8],"the":[9,46,54,70,74,118,121],"automation":[10],"of":[11,56,59,96,99,120],"spot":[12],"spraying":[13],"mechanical":[15],"weeding.":[16],"Previous":[17],"studies":[18],"developed":[19],"crop":[20,27,47,64,77,85,103],"methods":[24,31,71],"by":[25,53,101,112,123],"using":[26,106,124],"rows.":[28],"However,":[29],"those":[30],"cannot":[32],"perform":[33],"with":[34],"high":[35],"accuracy":[36],"when":[37],"weeds":[38,75,100],"are":[39],"heavily":[40],"present.":[41],"The":[42,115],"reason":[43],"that":[45],"row":[48,104],"adversely":[51],"affected":[52],"presence":[55,95],"large":[57,97],"amounts":[58,98],"weed.":[60],"And":[61],"even":[62],"if":[63],"rows":[65,78],"can":[66,91],"be":[67,92],"detected":[68],"accurately,":[69],"wrongly":[72],"label":[73],"within":[76],"as":[79],"crop.":[80],"Therefore,":[81],"we":[82],"propose":[83],"a":[84],"method":[89,122],"which":[90],"used":[93],"in":[94,127],"combining":[102],"depth":[107],"data":[108],"crop/weed":[110],"classification":[111],"k-means":[113],"clustering.":[114],"experiment":[116],"showed":[117],"effectiveness":[119],"images":[125],"taken":[126],"unweeded":[128],"cabbage":[129],"field.":[130]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}