{"id":"https://openalex.org/W2737251272","doi":"https://doi.org/10.1109/icra.2017.7989020","title":"Growth measurement of Tomato fruit based on whole image processing","display_name":"Growth measurement of Tomato fruit based on whole image processing","publication_year":2017,"publication_date":"2017-05-01","ids":{"openalex":"https://openalex.org/W2737251272","doi":"https://doi.org/10.1109/icra.2017.7989020","mag":"2737251272"},"language":"en","primary_location":{"id":"doi:10.1109/icra.2017.7989020","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icra.2017.7989020","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE International Conference on Robotics and Automation (ICRA)","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/A5043323310","display_name":"Rui Fukui","orcid":"https://orcid.org/0000-0002-3940-8279"},"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":"Rui Fukui","raw_affiliation_strings":["Department of Human and Engineered Environmental Studies Graduate, University of Tokyo, Kashiwa-shi, Chiba, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Human and Engineered Environmental Studies Graduate, University of Tokyo, Kashiwa-shi, Chiba, Japan","institution_ids":["https://openalex.org/I74801974"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5110601458","display_name":"Julien Schneider","orcid":null},"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":"Julien Schneider","raw_affiliation_strings":["Department of Human and Engineered Environmental Studies Graduate, University of Tokyo, Kashiwa-shi, Chiba, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Human and Engineered Environmental Studies Graduate, University of Tokyo, Kashiwa-shi, Chiba, Japan","institution_ids":["https://openalex.org/I74801974"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5063409251","display_name":"Tsurugi Nishioka","orcid":null},"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":"Tsurugi Nishioka","raw_affiliation_strings":["Department of Human and Engineered Environmental Studies Graduate, University of Tokyo, Kashiwa-shi, Chiba, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Human and Engineered Environmental Studies Graduate, University of Tokyo, Kashiwa-shi, Chiba, Japan","institution_ids":["https://openalex.org/I74801974"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081838259","display_name":"Shin\u2019ichi Warisawa","orcid":"https://orcid.org/0000-0001-9815-6801"},"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":"Shinichi Warisawa","raw_affiliation_strings":["Department of Human and Engineered Environmental Studies Graduate, University of Tokyo, Kashiwa-shi, Chiba, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Human and Engineered Environmental Studies Graduate, University of Tokyo, Kashiwa-shi, Chiba, Japan","institution_ids":["https://openalex.org/I74801974"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5050316548","display_name":"Ichiro Yamada","orcid":"https://orcid.org/0000-0001-5214-6309"},"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":"Ichiro Yamada","raw_affiliation_strings":["Department of Human and Engineered Environmental Studies Graduate, University of Tokyo, Kashiwa-shi, Chiba, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Human and Engineered Environmental Studies Graduate, University of Tokyo, Kashiwa-shi, Chiba, Japan","institution_ids":["https://openalex.org/I74801974"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I74801974"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"153","last_page":"158"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10616","display_name":"Smart Agriculture and AI","score":0.9994000196456909,"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":0.9994000196456909,"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":0.9958000183105469,"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":0.9883000254631042,"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/image-processing","display_name":"Image processing","score":0.5395644307136536},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5090250968933105},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5083915591239929},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4287962317466736},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.41860756278038025}],"concepts":[{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.5395644307136536},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5090250968933105},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5083915591239929},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4287962317466736},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.41860756278038025}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icra.2017.7989020","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icra.2017.7989020","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE International Conference on Robotics and Automation (ICRA)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":9,"referenced_works":["https://openalex.org/W1925668245","https://openalex.org/W1983016117","https://openalex.org/W2057248640","https://openalex.org/W2087616360","https://openalex.org/W2098185782","https://openalex.org/W2098976163","https://openalex.org/W2135046866","https://openalex.org/W2156585878","https://openalex.org/W4206070770"],"related_works":["https://openalex.org/W2005185696","https://openalex.org/W2080322084","https://openalex.org/W23451984","https://openalex.org/W2161229648","https://openalex.org/W3003164983","https://openalex.org/W2235753890","https://openalex.org/W2507763083","https://openalex.org/W2993674027","https://openalex.org/W3214851576","https://openalex.org/W2361114818"],"abstract_inverted_index":{"Crop":[0],"grow":[1],"measurement":[2,13],"technologies":[3],"are":[4,17,64],"important":[5],"to":[6,70,100,106,116],"increase":[7],"the":[8,34,72,78,101,108,111,118],"farm":[9],"productivity.":[10],"Detection":[11],"and":[12,21,114,127],"of":[14,59,77,110,123],"fruit":[15,35,73],"volume":[16],"useful":[18],"for":[19],"forecasting":[20],"harvesting":[22],"applications.":[23],"Some":[24],"environmental":[25],"challenges":[26],"such":[27],"as":[28,56],"lighting":[29],"conditions":[30],"or":[31],"occlusions":[32],"make":[33],"detection":[36],"difficult.":[37],"Our":[38],"approach":[39],"is":[40,84,89],"based":[41],"on":[42],"features":[43],"extraction":[44],"from":[45],"images":[46,53],"through":[47],"a":[48,57,67,93],"sub-image":[49],"clustering":[50],"technique.":[51],"Then":[52],"being":[54],"described":[55],"number":[58],"pixel":[60],"in":[61,66,81,92,121],"various":[62],"labels":[63],"used":[65],"regression":[68],"model":[69],"estimate":[71],"volume.":[74],"The":[75,87],"validity":[76],"proposed":[79,119],"method":[80,88,120],"experimental":[82],"condition":[83,95],"successfully":[85],"verified.":[86],"evaluated":[90],"also":[91],"field":[94],"but":[96],"results":[97],"were":[98],"inferior":[99],"expectation.":[102],"This":[103],"paper":[104],"tries":[105,115],"elucidate":[107],"reasons":[109],"insufficient":[112],"performance":[113],"improve":[117],"terms":[122],"illumination":[124],"condition,":[125],"precision":[126],"calculation":[128],"time.":[129]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":2}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
