{"id":"https://openalex.org/W4403920059","doi":"https://doi.org/10.1109/ro-man60168.2024.10731141","title":"Locating the Fruit to Be Harvested and Estimating Cut Positions from RGBD Images Acquired by a Camera Moved along Fixed Paths Using a Mask-R-CNN Based Method","display_name":"Locating the Fruit to Be Harvested and Estimating Cut Positions from RGBD Images Acquired by a Camera Moved along Fixed Paths Using a Mask-R-CNN Based Method","publication_year":2024,"publication_date":"2024-08-26","ids":{"openalex":"https://openalex.org/W4403920059","doi":"https://doi.org/10.1109/ro-man60168.2024.10731141"},"language":"en","primary_location":{"id":"doi:10.1109/ro-man60168.2024.10731141","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ro-man60168.2024.10731141","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 33rd IEEE International Conference on Robot and Human Interactive Communication (ROMAN)","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/A5100781928","display_name":"Wentao Zhao","orcid":"https://orcid.org/0009-0002-1530-8975"},"institutions":[{"id":"https://openalex.org/I150744194","display_name":"Waseda University","ror":"https://ror.org/00ntfnx83","country_code":"JP","type":"education","lineage":["https://openalex.org/I150744194"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Wentao Zhao","raw_affiliation_strings":["Waseda University,Department of Modern Mechanical Engineering,Tokyo,Japan,1690075"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Waseda University,Department of Modern Mechanical Engineering,Tokyo,Japan,1690075","institution_ids":["https://openalex.org/I150744194"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5050053184","display_name":"Takuya Otani","orcid":"https://orcid.org/0000-0002-5514-6037"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Takuya Otani","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5043946406","display_name":"S. R. Soma","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sugiyama Soma","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5114467563","display_name":"Mitani Kento","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Mitani Kento","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5045158803","display_name":"Koki Masaya","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Koki Masaya","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5075328170","display_name":"Atsuo Takanishi","orcid":"https://orcid.org/0009-0009-9388-9278"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Atsuo Takanishi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074591962","display_name":"Shuntaro Aotake","orcid":"https://orcid.org/0000-0003-1991-7428"},"institutions":[{"id":"https://openalex.org/I4210122684","display_name":"Sony Computer Science Laboratories","ror":"https://ror.org/02nc46417","country_code":"JP","type":"facility","lineage":["https://openalex.org/I4210122684"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Shuntaro Aotake","raw_affiliation_strings":["Sony Computer Science Laboratories, Inc.,Tokyo,Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Sony Computer Science Laboratories, Inc.,Tokyo,Japan","institution_ids":["https://openalex.org/I4210122684"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5060054789","display_name":"Masatoshi Funabashi","orcid":"https://orcid.org/0000-0002-7519-3084"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Masatoshi Funabashi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5111371620","display_name":"Jun Ohya","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jun Ohya","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"2189","last_page":"2196"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10616","display_name":"Smart Agriculture and AI","score":0.9948999881744385,"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":0.9948999881744385,"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/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.9847999811172485,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.9632999897003174,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.7134947776794434},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7016962766647339},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5878520607948303},{"id":"https://openalex.org/keywords/computer-graphics","display_name":"Computer graphics (images)","score":0.5256180167198181}],"concepts":[{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.7134947776794434},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7016962766647339},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5878520607948303},{"id":"https://openalex.org/C121684516","wikidata":"https://www.wikidata.org/wiki/Q7600677","display_name":"Computer graphics (images)","level":1,"score":0.5256180167198181}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ro-man60168.2024.10731141","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ro-man60168.2024.10731141","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 33rd IEEE International Conference on Robot and Human Interactive Communication (ROMAN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.4099999964237213,"id":"https://metadata.un.org/sdg/2","display_name":"Zero hunger"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320321034","display_name":"New Energy and Industrial Technology Development Organization","ror":"https://ror.org/0055k7a87"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W2337459181","https://openalex.org/W2910612977","https://openalex.org/W2963150697","https://openalex.org/W2966926453","https://openalex.org/W2989676862","https://openalex.org/W2993182889","https://openalex.org/W2999278897","https://openalex.org/W3003545971","https://openalex.org/W3017064301","https://openalex.org/W3030176837","https://openalex.org/W3161327649","https://openalex.org/W3202112348","https://openalex.org/W4206060409","https://openalex.org/W4313574145","https://openalex.org/W4382359410"],"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":{"Compared":[0],"to":[1,84],"traditional":[2],"agricultural":[3],"environments,":[4],"the":[5,50,74,78,85,89,97,106,117,158],"high":[6,164],"density":[7],"and":[8,21,25,48,69,81,91,120,142,151],"diversity":[9],"of":[10,66,110],"vegetation":[11],"layouts":[12],"in":[13,19,113,146],"Synecoculture":[14],"farms":[15],"present":[16],"significant":[17],"challenges":[18],"locating":[20,41],"harvesting":[22,103,121,165],"occluded":[23,99,140,160],"fruits":[24,42,68,112],"pedicels":[26,51],"(cutting":[27],"points).":[28],"To":[29],"address":[30],"this":[31,33,71,94,126,136],"challenge,":[32],"study":[34],"proposes":[35],"a":[36,57,130,163],"Mask":[37],"R-CNN-based":[38],"method":[39,72,137,155],"for":[40,102,162],"(tomatoes,":[43],"yellow":[44],"bell":[45],"peppers,":[46],"etc.)":[47],"estimating":[49],"from":[52,125],"RGBD":[53],"images":[54,114],"acquired":[55,115],"by":[56],"camera":[58],"moved":[59],"along":[60],"fixed":[61,118],"paths.":[62],"After":[63],"obtaining":[64],"masks":[65],"all":[67],"pedicels,":[70],"judges":[73],"matching":[75],"relationship":[76],"between":[77,88],"located":[79,111],"fruit":[80,90],"pedicel":[82],"according":[83],"3D":[86],"distance":[87],"pedicel.":[92],"Subsequently,":[93],"research":[95],"determines":[96],"least":[98,159],"best":[100,127],"viewpoint":[101,128,161],"based":[104],"on":[105],"visible":[107],"real":[108],"areas":[109],"under":[116],"paths,":[119],"is":[122],"then":[123],"completed":[124],"following":[129],"straight":[131],"path.":[132],"Experimental":[133],"results":[134],"show":[135],"effectively":[138],"identifies":[139],"targets":[141],"their":[143],"cutting":[144],"positions":[145],"both":[147],"Gazebo":[148],"simulation":[149],"environments":[150],"real-world":[152],"farms.":[153],"This":[154],"can":[156],"select":[157],"success":[166],"rate.":[167]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}