{"id":"https://openalex.org/W3197875528","doi":"https://doi.org/10.3390/e23091160","title":"A Crop Image Segmentation and Extraction Algorithm Based on Mask RCNN","display_name":"A Crop Image Segmentation and Extraction Algorithm Based on Mask RCNN","publication_year":2021,"publication_date":"2021-09-03","ids":{"openalex":"https://openalex.org/W3197875528","doi":"https://doi.org/10.3390/e23091160","mag":"3197875528","pmid":"https://pubmed.ncbi.nlm.nih.gov/34573785"},"language":"en","primary_location":{"id":"doi:10.3390/e23091160","is_oa":true,"landing_page_url":"https://doi.org/10.3390/e23091160","pdf_url":"https://www.mdpi.com/1099-4300/23/9/1160/pdf?version=1630894209","source":{"id":"https://openalex.org/S195231649","display_name":"Entropy","issn_l":"1099-4300","issn":["1099-4300"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Entropy","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/1099-4300/23/9/1160/pdf?version=1630894209","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5069998729","display_name":"Shijie Wang","orcid":"https://orcid.org/0000-0003-1716-838X"},"institutions":[{"id":"https://openalex.org/I205237279","display_name":"Nankai University","ror":"https://ror.org/01y1kjr75","country_code":"CN","type":"education","lineage":["https://openalex.org/I205237279"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shijie Wang","raw_affiliation_strings":["College of Electronic Information and Optical Engineering, Nankai University, Tianjin 300350, China"],"raw_orcid":"https://orcid.org/0000-0003-1716-838X","affiliations":[{"raw_affiliation_string":"College of Electronic Information and Optical Engineering, Nankai University, Tianjin 300350, China","institution_ids":["https://openalex.org/I205237279"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101701886","display_name":"Guiling Sun","orcid":"https://orcid.org/0000-0001-5283-1760"},"institutions":[{"id":"https://openalex.org/I205237279","display_name":"Nankai University","ror":"https://ror.org/01y1kjr75","country_code":"CN","type":"education","lineage":["https://openalex.org/I205237279"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Guiling Sun","raw_affiliation_strings":["College of Electronic Information and Optical Engineering, Nankai University, Tianjin 300350, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Electronic Information and Optical Engineering, Nankai University, Tianjin 300350, China","institution_ids":["https://openalex.org/I205237279"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Bowen Zheng","orcid":"https://orcid.org/0000-0003-4536-8215"},"institutions":[{"id":"https://openalex.org/I205237279","display_name":"Nankai University","ror":"https://ror.org/01y1kjr75","country_code":"CN","type":"education","lineage":["https://openalex.org/I205237279"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bowen Zheng","raw_affiliation_strings":["College of Electronic Information and Optical Engineering, Nankai University, Tianjin 300350, China"],"raw_orcid":"https://orcid.org/0000-0003-4536-8215","affiliations":[{"raw_affiliation_string":"College of Electronic Information and Optical Engineering, Nankai University, Tianjin 300350, China","institution_ids":["https://openalex.org/I205237279"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5058042531","display_name":"Ya-Wen Du","orcid":"https://orcid.org/0000-0002-1298-1737"},"institutions":[{"id":"https://openalex.org/I205237279","display_name":"Nankai University","ror":"https://ror.org/01y1kjr75","country_code":"CN","type":"education","lineage":["https://openalex.org/I205237279"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yawen Du","raw_affiliation_strings":["College of Electronic Information and Optical Engineering, Nankai University, Tianjin 300350, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Electronic Information and Optical Engineering, Nankai University, Tianjin 300350, China","institution_ids":["https://openalex.org/I205237279"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5101701886"],"corresponding_institution_ids":["https://openalex.org/I205237279"],"apc_list":{"value":2000,"currency":"CHF","value_usd":2165},"apc_paid":{"value":2000,"currency":"CHF","value_usd":2165},"fwci":12.0898,"has_fulltext":true,"cited_by_count":82,"citation_normalized_percentile":{"value":0.98724601,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":100},"biblio":{"volume":"23","issue":"9","first_page":"1160","last_page":"1160"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10616","display_name":"Smart Agriculture and AI","score":0.9976999759674072,"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":0.9976999759674072,"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":0.9345999956130981,"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/T11019","display_name":"Image Enhancement Techniques","score":0.9308000206947327,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7140387296676636},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7081207036972046},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5669434070587158},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4963598847389221},{"id":"https://openalex.org/keywords/sobel-operator","display_name":"Sobel operator","score":0.48040178418159485},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.4534960687160492},{"id":"https://openalex.org/keywords/edge-detection","display_name":"Edge detection","score":0.4317547678947449},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4279845058917999},{"id":"https://openalex.org/keywords/test-set","display_name":"Test set","score":0.42472606897354126},{"id":"https://openalex.org/keywords/precision-and-recall","display_name":"Precision and recall","score":0.4141501188278198},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4134480357170105},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.39613616466522217},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.35587018728256226},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.3265746533870697},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.32641565799713135}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7140387296676636},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7081207036972046},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5669434070587158},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4963598847389221},{"id":"https://openalex.org/C30703548","wikidata":"https://www.wikidata.org/wiki/Q1757673","display_name":"Sobel operator","level":5,"score":0.48040178418159485},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.4534960687160492},{"id":"https://openalex.org/C193536780","wikidata":"https://www.wikidata.org/wiki/Q1513153","display_name":"Edge detection","level":4,"score":0.4317547678947449},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4279845058917999},{"id":"https://openalex.org/C169903167","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Test set","level":2,"score":0.42472606897354126},{"id":"https://openalex.org/C81669768","wikidata":"https://www.wikidata.org/wiki/Q2359161","display_name":"Precision and recall","level":2,"score":0.4141501188278198},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4134480357170105},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.39613616466522217},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.35587018728256226},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.3265746533870697},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.32641565799713135},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":6,"locations":[{"id":"doi:10.3390/e23091160","is_oa":true,"landing_page_url":"https://doi.org/10.3390/e23091160","pdf_url":"https://www.mdpi.com/1099-4300/23/9/1160/pdf?version=1630894209","source":{"id":"https://openalex.org/S195231649","display_name":"Entropy","issn_l":"1099-4300","issn":["1099-4300"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Entropy","raw_type":"journal-article"},{"id":"pmid:34573785","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/34573785","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Entropy (Basel, Switzerland)","raw_type":null},{"id":"pmh:oai:doaj.org/article:a53aa88c01ef4de48e04978925bffb7d","is_oa":true,"landing_page_url":"https://doaj.org/article/a53aa88c01ef4de48e04978925bffb7d","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","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":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Entropy, Vol 23, Iss 9, p 1160 (2021)","raw_type":"article"},{"id":"pmh:oai:europepmc.org:7357895","is_oa":true,"landing_page_url":"http://europepmc.org/pmc/articles/PMC8469590","pdf_url":null,"source":{"id":"https://openalex.org/S4306400806","display_name":"Europe PMC (PubMed Central)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1303153112","host_organization_name":"European Bioinformatics Institute","host_organization_lineage":["https://openalex.org/I1303153112"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Text"},{"id":"pmh:oai:mdpi.com:/1099-4300/23/9/1160/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/e23091160","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Entropy; Volume 23; Issue 9; Pages: 1160","raw_type":"Text"},{"id":"pmh:oai:pubmedcentral.nih.gov:8469590","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/8469590","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Entropy (Basel)","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/e23091160","is_oa":true,"landing_page_url":"https://doi.org/10.3390/e23091160","pdf_url":"https://www.mdpi.com/1099-4300/23/9/1160/pdf?version=1630894209","source":{"id":"https://openalex.org/S195231649","display_name":"Entropy","issn_l":"1099-4300","issn":["1099-4300"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Entropy","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.6899999976158142,"id":"https://metadata.un.org/sdg/2","display_name":"Zero hunger"}],"awards":[{"id":"https://openalex.org/G3106587967","display_name":null,"funder_award_id":"No. 61771262","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3141261596","display_name":"\u878d\u5408\u538b\u7f29\u611f\u77e5\u4e0e\u4f4e\u79e9\u7406\u8bba\u7684\u65e0\u7ebf\u4f20\u611f\u5668\u7f51\u7edc\u56fe\u50cf\u83b7\u53d6\u5173\u952e\u6280\u672f\u7684\u7814\u7a76","funder_award_id":"61771262","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3197875528.pdf","grobid_xml":"https://content.openalex.org/works/W3197875528.grobid-xml"},"referenced_works_count":24,"referenced_works":["https://openalex.org/W2140962554","https://openalex.org/W2290701356","https://openalex.org/W2555182955","https://openalex.org/W2586807479","https://openalex.org/W2783820472","https://openalex.org/W2888933900","https://openalex.org/W2890862129","https://openalex.org/W2891656133","https://openalex.org/W2912697496","https://openalex.org/W2947760388","https://openalex.org/W2952555815","https://openalex.org/W2963150697","https://openalex.org/W2998957378","https://openalex.org/W3002714426","https://openalex.org/W3039201839","https://openalex.org/W3095502485","https://openalex.org/W3118053069","https://openalex.org/W3132455321","https://openalex.org/W3133849452","https://openalex.org/W3159433923","https://openalex.org/W3162980553","https://openalex.org/W3165664581","https://openalex.org/W3171926713","https://openalex.org/W6780041003"],"related_works":["https://openalex.org/W4388400392","https://openalex.org/W2383455043","https://openalex.org/W1974517722","https://openalex.org/W2367735169","https://openalex.org/W2269083758","https://openalex.org/W4225576506","https://openalex.org/W2545393398","https://openalex.org/W2378692644","https://openalex.org/W2412868618","https://openalex.org/W3212250818"],"abstract_inverted_index":{"The":[0,115],"wide":[1],"variety":[2],"of":[3,8,118,135,152,213],"crops":[4,27],"in":[5,129,196,201],"the":[6,12,15,48,58,65,88,102,119,125,132,136,149,153,157,162,167,171,185,190,202],"image":[7,182,215],"agricultural":[9],"products":[10],"and":[11,29,73,94,97,111,165,177,180,210],"confusion":[13],"with":[14,55,175],"surrounding":[16],"environment":[17],"information":[18,117],"makes":[19],"it":[20],"difficult":[21],"for":[22,40],"traditional":[23],"methods":[24],"to":[25,101,148,160,170],"extract":[26],"accurately":[28],"efficiently.":[30],"In":[31],"this":[32,197],"paper,":[33],"an":[34,78],"automatic":[35],"extraction":[36,109,183,216],"algorithm":[37,194],"is":[38,53,62,85,122,139,199],"proposed":[39,195],"crop":[41,214],"images":[42],"based":[43],"on":[44],"Mask":[45,80,178,192],"RCNN.":[46],"First,":[47],"Fruits":[49,59],"360":[50,60],"Dataset":[51,61],"label":[52],"set":[54,72],"Labelme.":[56],"Then,":[57],"preprocessed.":[63],"Next,":[64],"data":[66],"are":[67,99],"divided":[68],"into":[69],"a":[70,74,144],"training":[71],"test":[75],"set.":[76],"Additionally,":[77],"improved":[79,141,191],"RCNN":[81,179,193],"network":[82,103],"model":[83],"structure":[84],"established":[86],"using":[87],"PyTorch":[89],"1.8.1":[90],"deep":[91],"learning":[92],"framework,":[93],"path":[95],"aggregation":[96],"features":[98],"added":[100],"design":[104],"enhanced":[105],"functions,":[106],"optimized":[107],"region":[108],"network,":[110],"feature":[112,120],"pyramid":[113],"network.":[114],"spatial":[116],"map":[121],"saved":[123],"by":[124,142],"bilinear":[126],"interpolation":[127],"method":[128],"ROIAlign.":[130],"Finally,":[131],"edge":[133,168],"accuracy":[134],"segmentation":[137],"mask":[138,150],"further":[140],"adding":[143,166],"micro-fully":[145],"connected":[146],"layer":[147],"branch":[151],"ROI":[154],"output,":[155],"employing":[156],"Sobel":[158],"operator":[159],"predict":[161],"target":[163],"edge,":[164],"loss":[169,172],"function.":[173],"Compared":[174],"FCN":[176],"other":[181],"algorithms,":[184],"experimental":[186],"results":[187],"demonstrate":[188],"that":[189],"paper":[198],"better":[200],"precision,":[203,206],"Recall,":[204],"Average":[205,208],"Mean":[207],"Precision,":[209],"F1":[211],"scores":[212],"results.":[217]},"counts_by_year":[{"year":2026,"cited_by_count":4},{"year":2025,"cited_by_count":20},{"year":2024,"cited_by_count":18},{"year":2023,"cited_by_count":30},{"year":2022,"cited_by_count":9},{"year":2018,"cited_by_count":1}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}
