{"id":"https://openalex.org/W2945103221","doi":"https://doi.org/10.1145/3318299.3318338","title":"A Robust Mature Tomato Detection in Greenhouse Scenes Using Machine Learning and Color Analysis","display_name":"A Robust Mature Tomato Detection in Greenhouse Scenes Using Machine Learning and Color Analysis","publication_year":2019,"publication_date":"2019-02-22","ids":{"openalex":"https://openalex.org/W2945103221","doi":"https://doi.org/10.1145/3318299.3318338","mag":"2945103221"},"language":"en","primary_location":{"id":"doi:10.1145/3318299.3318338","doi":"https://doi.org/10.1145/3318299.3318338","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3318299.3318338","pdf_url":null,"source":{"id":"https://openalex.org/S7407088508","display_name":"International Conference on Machine Learning and Computing (ICMLC)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":"Proceedings of the 2019 11th International Conference on Machine Learning and Computing","raw_type":"proceedings-article"},"volume":null,"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/A5027329210","display_name":"Guoxu Liu","orcid":"https://orcid.org/0000-0002-3668-4569","observed_orcids":["https://orcid.org/0000-0002-3668-4569"]},"institutions":[{"id":"https://openalex.org/I4210136047","display_name":"Weifang University of Science and Technology","ror":"https://ror.org/04ha2bb10","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210136047"]},{"id":"https://openalex.org/I4921948","display_name":"Pusan National University","ror":"https://ror.org/01an57a31","country_code":"KR","type":"education","lineage":["https://openalex.org/I4921948"]}],"countries":["CN","KR"],"is_corresponding":false,"raw_author_name":"Guoxu Liu","raw_affiliation_strings":["Dept. of Electronics Engineering, Pusan National University, Busan, Rep. of Korea and Computer Software Institute, Weifang University of Science &amp; Technology, Shouguang, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dept. of Electronics Engineering, Pusan National University, Busan, Rep. of Korea and Computer Software Institute, Weifang University of Science &amp; Technology, Shouguang, China","institution_ids":["https://openalex.org/I4210136047","https://openalex.org/I4921948"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5047393648","display_name":"Shuyi Mao","orcid":"https://orcid.org/0000-0002-7529-917X","observed_orcids":["https://orcid.org/0000-0002-7529-917X"]},"institutions":[{"id":"https://openalex.org/I4921948","display_name":"Pusan National University","ror":"https://ror.org/01an57a31","country_code":"KR","type":"education","lineage":["https://openalex.org/I4921948"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Shuyi Mao","raw_affiliation_strings":["Dept. of Electronics Engineering, Pusan National University, Busan, Rep. of Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dept. of Electronics Engineering, Pusan National University, Busan, Rep. of Korea","institution_ids":["https://openalex.org/I4921948"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Hui Jin","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I4921948","display_name":"Pusan National University","ror":"https://ror.org/01an57a31","country_code":"KR","type":"education","lineage":["https://openalex.org/I4921948"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Hui Jin","raw_affiliation_strings":["Dept. of Electronics Engineering, Pusan National University, Busan, Rep. of Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dept. of Electronics Engineering, Pusan National University, Busan, Rep. of Korea","institution_ids":["https://openalex.org/I4921948"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100649967","display_name":"Jae Ho Kim","orcid":"https://orcid.org/0000-0003-4323-4790","observed_orcids":["https://orcid.org/0000-0003-4323-4790"]},"institutions":[{"id":"https://openalex.org/I4921948","display_name":"Pusan National University","ror":"https://ror.org/01an57a31","country_code":"KR","type":"education","lineage":["https://openalex.org/I4921948"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Jae Ho Kim","raw_affiliation_strings":["Dept. of Electronics Engineering, Pusan National University, Busan, Rep. of Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dept. of Electronics Engineering, Pusan National University, Busan, Rep. of Korea","institution_ids":["https://openalex.org/I4921948"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":3.8083,"has_fulltext":false,"cited_by_count":10,"citation_normalized_percentile":{"value":0.93776757,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"17","last_page":"21"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10616","display_name":"Smart Agriculture and AI","score":0.9980000257492065,"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":0.9980000257492065,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.0012000000569969416,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.00019999999494757503,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/tomato-detection","display_name":"tomato detection","score":0.9070000052452087},{"id":"https://openalex.org/keywords/greenhouse","display_name":"greenhouse","score":0.4440000057220459},{"id":"https://openalex.org/keywords/object-detection","display_name":"object detection","score":0.7429999709129333},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"support vector machine","score":0.906000018119812},{"id":"https://openalex.org/keywords/histogram-of-oriented-gradients","display_name":"histogram of oriented gradients","score":0.972000002861023},{"id":"https://openalex.org/keywords/color-analysis","display_name":"color analysis","score":0.8799999952316284},{"id":"https://openalex.org/keywords/false-positive-removal","display_name":"false positive elimination","score":0.9390000104904175},{"id":"https://openalex.org/keywords/non-maximum-suppression","display_name":"non-maximum suppression","score":0.9829999804496765},{"id":"https://openalex.org/keywords/occlusion","display_name":"occlusion","score":0.6449999809265137},{"id":"https://openalex.org/keywords/illumination-robustness","display_name":"illumination robustness","score":0.828000009059906}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7796928882598877},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.71938556432724},{"id":"https://openalex.org/C53533937","wikidata":"https://www.wikidata.org/wiki/Q185020","display_name":"Histogram","level":3,"score":0.6682363748550415},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6350187063217163},{"id":"https://openalex.org/C197129107","wikidata":"https://www.wikidata.org/wiki/Q1921621","display_name":"Merge (version control)","level":2,"score":0.6243223547935486},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6114864349365234},{"id":"https://openalex.org/C81669768","wikidata":"https://www.wikidata.org/wiki/Q2359161","display_name":"Precision and recall","level":2,"score":0.5300284028053284},{"id":"https://openalex.org/C17426736","wikidata":"https://www.wikidata.org/wiki/Q419918","display_name":"Histogram of oriented gradients","level":4,"score":0.5130449533462524},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.47259435057640076},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.4175412058830261},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.10022705793380737},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3318299.3318338","doi":"https://doi.org/10.1145/3318299.3318338","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3318299.3318338","pdf_url":null,"source":{"id":"https://openalex.org/S7407088508","display_name":"International Conference on Machine Learning and Computing (ICMLC)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":"Proceedings of the 2019 11th International Conference on Machine Learning and Computing","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6875,"id":"https://metadata.un.org/sdg/2","display_name":"Zero hunger"}],"study_designs":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321284","display_name":"Pusan National University","ror":"https://ror.org/01an57a31"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W947585488","https://openalex.org/W1974962742","https://openalex.org/W1976847732","https://openalex.org/W1986235237","https://openalex.org/W2019168270","https://openalex.org/W2064352738","https://openalex.org/W2072364589","https://openalex.org/W2087347434","https://openalex.org/W2094766409","https://openalex.org/W2106556101","https://openalex.org/W2161969291","https://openalex.org/W2413122674","https://openalex.org/W2467954037","https://openalex.org/W2472556136","https://openalex.org/W4239510810"],"related_works":["https://openalex.org/W2942551514","https://openalex.org/W4285240989","https://openalex.org/W4385882388","https://openalex.org/W3112680371","https://openalex.org/W3021835960","https://openalex.org/W6990509930","https://openalex.org/W2413122674","https://openalex.org/W1977573024","https://openalex.org/W2414021343","https://openalex.org/W1979194830"],"abstract_inverted_index":{"A":[0],"new":[1],"algorithm":[2,111],"for":[3,54,79,115],"automatic":[4],"tomato":[5,116],"detection":[6,69],"in":[7,106],"regular":[8],"color":[9,20,51],"images":[10,76],"is":[11,64],"proposed,":[12],"which":[13],"can":[14],"reduce":[15],"the":[16,26,46,59,68,80,86,91,98,109],"influence":[17],"of":[18,28,40,74,90],"illumination,":[19],"similarity":[21],"as":[22,24],"well":[23],"suppress":[25],"effect":[27],"occlusion.":[29],"The":[30,82],"method":[31,53],"uses":[32],"a":[33,50,72],"Support":[34],"Vector":[35],"Machine":[36],"(SVM)":[37],"with":[38,102],"Histograms":[39],"Oriented":[41],"Gradients":[42],"(HOG)":[43],"to":[44,66],"detect":[45],"tomatoes,":[47],"followed":[48],"by":[49],"analysis":[52],"false":[55],"positive":[56],"removal.":[57],"And":[58],"Non-Maximum":[60],"Suppression":[61],"Method":[62],"(NMS)":[63],"employed":[65],"merge":[67],"results.":[70],"Finally,":[71],"total":[73],"144":[75],"were":[77,93],"used":[78],"experiment.":[81],"results":[83],"showed":[84],"that":[85],"recall":[87],"and":[88,95],"precision":[89],"classifier":[92],"96.67%":[94],"98.64%":[96],"on":[97],"test":[99],"set.":[100],"Compared":[101],"other":[103],"methods":[104],"developed":[105],"recent":[107],"years,":[108],"proposed":[110],"shows":[112],"substantial":[113],"improvement":[114],"detection.":[117]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":5},{"year":2021,"cited_by_count":2},{"year":2019,"cited_by_count":1}],"updated_date":"2026-10-14T16:39:01.820549","created_date":"2019-05-29T00:00:00"}
