{"id":"https://openalex.org/W7225123175","doi":"https://doi.org/10.1038/s41598-026-76200-w","title":"Boundary-weighted supervision and multi-scale context enhancement for greenhouse tomato instance segmentation using YOLO11n-seg","display_name":"Boundary-weighted supervision and multi-scale context enhancement for greenhouse tomato instance segmentation using YOLO11n-seg","publication_year":2026,"publication_date":"2026-11-02","ids":{"openalex":"https://openalex.org/W7225123175","doi":"https://doi.org/10.1038/s41598-026-76200-w"},"language":"en","primary_location":{"id":"doi:10.1038/s41598-026-76200-w","doi":"https://doi.org/10.1038/s41598-026-76200-w","is_oa":true,"landing_page_url":"https://doi.org/10.1038/s41598-026-76200-w","pdf_url":"https://www.nature.com/articles/s41598-026-76200-w_reference.pdf","source":{"id":"https://openalex.org/S196734849","display_name":"Scientific Reports","issn_l":"2045-2322","issn":["2045-2322"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["anvur-class-a","anvur-scientific","cwts-core","doaj","dongbi-c","doyens","jufo-1","ki-jl-1","medline","norway-1","poland-140","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310319908","host_organization_name":"Nature Portfolio","host_organization_lineage":["https://openalex.org/P4310319908","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Nature Portfolio","Springer Nature"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Scientific Reports","raw_type":"journal-article"},"volume":null,"type":"article","is_traditional":true,"indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.nature.com/articles/s41598-026-76200-w_reference.pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5146114869","display_name":"Jinlong Chen","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I5343935","display_name":"Guilin University of Electronic Technology","ror":"https://ror.org/05arjae42","country_code":"CN","type":"education","lineage":["https://openalex.org/I5343935"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jinlong Chen","raw_affiliation_strings":["School of Computer Science and Information Security, Guilin University of Electronic Technology, Guilin, 541004, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Information Security, Guilin University of Electronic Technology, Guilin, 541004, China","institution_ids":["https://openalex.org/I5343935"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112125002","display_name":"Jiatao Xiong","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I5343935","display_name":"Guilin University of Electronic Technology","ror":"https://ror.org/05arjae42","country_code":"CN","type":"education","lineage":["https://openalex.org/I5343935"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiatao Xiong","raw_affiliation_strings":["School of Computer Science and Information Security, Guilin University of Electronic Technology, Guilin, 541004, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Information Security, Guilin University of Electronic Technology, Guilin, 541004, China","institution_ids":["https://openalex.org/I5343935"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5160324399","display_name":"Minghao Yang","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210112150","display_name":"Institute of Automation","ror":"https://ror.org/022c3hy66","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210112150"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Minghao Yang","raw_affiliation_strings":["Research Center for Brain-Inspired Intelligence, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Research Center for Brain-Inspired Intelligence, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, China","institution_ids":["https://openalex.org/I19820366","https://openalex.org/I4210112150"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5030607500","display_name":"Wujun Che","orcid":"https://orcid.org/0000-0001-8230-0696","observed_orcids":["https://orcid.org/0000-0001-8230-0696"]},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wujun Che","raw_affiliation_strings":["Key Laboratory of Multimodal Artificial Intelligence Systems, Chinese Academy of Sciences, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Key Laboratory of Multimodal Artificial Intelligence Systems, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5126577548","display_name":"Shengsheng Wang","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I167383011","display_name":"Henan University of Science and Technology","ror":"https://ror.org/05d80kz58","country_code":"CN","type":"education","lineage":["https://openalex.org/I167383011"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shengsheng Wang","raw_affiliation_strings":["College of Agricultural Equipment Engineering, Henan University of Science and Technology, Luoyang, 471003, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Agricultural Equipment Engineering, Henan University of Science and Technology, Luoyang, 471003, China","institution_ids":["https://openalex.org/I167383011"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5160355947","display_name":"Jun Zheng","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jun Zheng","raw_affiliation_strings":["Control Theory and Engineering, Taizhou Institute of Zhejiang University, Taizhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Control Theory and Engineering, Taizhou Institute of Zhejiang University, Taizhou, China","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101715358","display_name":"Yongsong Zhan","orcid":"https://orcid.org/0000-0003-1616-6868","observed_orcids":["https://orcid.org/0000-0003-1616-6868"]},"institutions":[{"id":"https://openalex.org/I5343935","display_name":"Guilin University of Electronic Technology","ror":"https://ror.org/05arjae42","country_code":"CN","type":"education","lineage":["https://openalex.org/I5343935"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yongsong Zhan","raw_affiliation_strings":["School of Computer Science and Information Security, Guilin University of Electronic Technology, Guilin, 541004, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Information Security, Guilin University of Electronic Technology, Guilin, 541004, China","institution_ids":["https://openalex.org/I5343935"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5108329071","display_name":"Yi Ning","orcid":"https://orcid.org/0009-0004-1611-8860","observed_orcids":["https://orcid.org/0009-0004-1611-8860"]},"institutions":[{"id":"https://openalex.org/I5343935","display_name":"Guilin University of Electronic Technology","ror":"https://ror.org/05arjae42","country_code":"CN","type":"education","lineage":["https://openalex.org/I5343935"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yi Ning","raw_affiliation_strings":["School of Computer Science and Information Security, Guilin University of Electronic Technology, Guilin, 541004, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Information Security, Guilin University of Electronic Technology, Guilin, 541004, China","institution_ids":["https://openalex.org/I5343935"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5101715358","https://openalex.org/A5108329071"],"corresponding_institution_ids":["https://openalex.org/I5343935"],"apc_list":{"value":2690,"currency":"USD","value_usd":2690},"apc_paid":{"value":2690,"currency":"USD","value_usd":2690},"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.82216967,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10616","display_name":"Smart Agriculture and AI","score":0.8529999852180481,"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":0.8529999852180481,"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":0.1460999995470047,"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":9.999999747378752e-05,"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/greenhouse-crops","display_name":"greenhouse crops","score":0.6200000047683716},{"id":"https://openalex.org/keywords/plant-detection","display_name":"plant detection","score":0.4560000002384186}],"concepts":[{"id":"https://openalex.org/C32198211","wikidata":"https://www.wikidata.org/wiki/Q165044","display_name":"Greenhouse","level":2,"score":0.6643999814987183},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6608999967575073},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6370999813079834},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.6323999762535095},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4943000078201294},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.38530001044273376},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3634999990463257},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.28839999437332153},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.2612999975681305},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.260699987411499},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.25}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1038/s41598-026-76200-w","doi":"https://doi.org/10.1038/s41598-026-76200-w","is_oa":true,"landing_page_url":"https://doi.org/10.1038/s41598-026-76200-w","pdf_url":"https://www.nature.com/articles/s41598-026-76200-w_reference.pdf","source":{"id":"https://openalex.org/S196734849","display_name":"Scientific Reports","issn_l":"2045-2322","issn":["2045-2322"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["anvur-class-a","anvur-scientific","cwts-core","doaj","dongbi-c","doyens","jufo-1","ki-jl-1","medline","norway-1","poland-140","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310319908","host_organization_name":"Nature Portfolio","host_organization_lineage":["https://openalex.org/P4310319908","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Nature Portfolio","Springer Nature"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Scientific Reports","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1038/s41598-026-76200-w","doi":"https://doi.org/10.1038/s41598-026-76200-w","is_oa":true,"landing_page_url":"https://doi.org/10.1038/s41598-026-76200-w","pdf_url":"https://www.nature.com/articles/s41598-026-76200-w_reference.pdf","source":{"id":"https://openalex.org/S196734849","display_name":"Scientific Reports","issn_l":"2045-2322","issn":["2045-2322"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["anvur-class-a","anvur-scientific","cwts-core","doaj","dongbi-c","doyens","jufo-1","ki-jl-1","medline","norway-1","poland-140","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310319908","host_organization_name":"Nature Portfolio","host_organization_lineage":["https://openalex.org/P4310319908","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Nature Portfolio","Springer Nature"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Scientific Reports","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/2","display_name":"Zero hunger","score":0.5666999816894531}],"study_designs":[],"awards":[{"id":"https://openalex.org/G1951034100","display_name":null,"funder_award_id":"AB24010164","funder_id":"https://openalex.org/F4320336589","funder_display_name":"Guangxi Key Research and Development Program"},{"id":"https://openalex.org/G3402442313","display_name":null,"funder_award_id":"AB25069476","funder_id":"https://openalex.org/F4320336589","funder_display_name":"Guangxi Key Research and Development Program"}],"funders":[{"id":"https://openalex.org/F4320336589","display_name":"Guangxi Key Research and Development Program","ror":null}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7225123175.pdf","grobid_xml":"https://content.openalex.org/works/W7225123175.grobid-xml"},"referenced_works_count":12,"referenced_works":["https://openalex.org/W2789804996","https://openalex.org/W2796347433","https://openalex.org/W3018757597","https://openalex.org/W3170019900","https://openalex.org/W4300978573","https://openalex.org/W4377971262","https://openalex.org/W4385686754","https://openalex.org/W4404344164","https://openalex.org/W4415795831","https://openalex.org/W7133196671","https://openalex.org/W7160257734","https://openalex.org/W7162571664"],"related_works":["https://openalex.org/W4415361552","https://openalex.org/W7202395529","https://openalex.org/W7167465404","https://openalex.org/W7202130582","https://openalex.org/W7128153956","https://openalex.org/W7119023055","https://openalex.org/W7213909314","https://openalex.org/W4405092999","https://openalex.org/W4410040475","https://openalex.org/W7075860087"],"abstract_inverted_index":{"Accurate":[0],"tomato":[1],"instance":[2,13,58],"segmentation":[3],"in":[4],"greenhouse":[5],"scenes":[6],"remains":[7,306],"challenging":[8],"because":[9],"of":[10,63,84,159,168,224,232,283,292],"fruit":[11],"occlusion,":[12],"contact,":[14],"ambiguous":[15],"boundaries,":[16],"and":[17,24,59,118,152,161,212,226,255,271,296,303],"the":[18,42,61,67,74,82,85,98,106,142,149,180,186,193,204,216,267],"visual":[19],"similarity":[20],"between":[21],"green":[22],"fruits":[23],"leaves.":[25],"This":[26],"study":[27],"presents":[28],"a":[29,35,51,165,174,221,227,275,280],"lightweight":[30,176],"YOLO11n-seg":[31,86,211],"framework":[32],"that":[33],"combines":[34],"morphology-based":[36],"shape-boundary-driven":[37],"(SBD)":[38],"weighting":[39,295],"strategy":[40],"with":[41,146,239,286],"previously":[43],"proposed":[44,217],"CMPRD":[45,78],"multi-scale":[46,90],"context":[47],"module.":[48],"SBD":[49],"constructs":[50],"narrow":[52],"contour":[53],"band":[54],"for":[55,210,215,288],"each":[56],"ground-truth":[57],"increases":[60,109,247,258],"contribution":[62],"boundary":[64,294],"pixels":[65],"to":[66,88,115,124,128,137,220,251,262],"mask":[68,240],"loss":[69],"during":[70],"training":[71],"without":[72],"altering":[73],"inference":[75],"graph,":[76],"whereas":[77,164],"replaces":[79],"SPPF":[80],"near":[81],"end":[83],"backbone":[87],"enhance":[89],"contextual":[91],"representation.":[92],"Across":[93],"five":[94,200],"independent":[95],"runs":[96,201],"on":[97],"128-image":[99],"validation":[100,269],"split":[101,270],"(mean":[102],"\u00b1":[103,195],"standard":[104,196],"deviation),":[105],"combined":[107],"model":[108],"Mask":[110,119,131,156,188,281],"Recall":[111],"from":[112,121,134,248,259],"\\(0.7656\\pm":[113],"0.0046\\)":[114],"\\(0.7726\\pm":[116],"0.0039\\)":[117],"mAP50\u201395":[120,157,189,282],"\\(0.6587\\pm":[122],"0.0025\\)":[123],"\\(0.6812\\pm":[125],"0.0026\\)":[126],"relative":[127],"YOLO11n-seg,":[129],"while":[130],"Precision":[132],"changes":[133],"\\(0.7989\\pm":[135],"0.0037\\)":[136],"\\(0.7961\\pm":[138],"0.0035\\)":[139],".":[140,265],"In":[141],"fixed":[143],"seed-0":[144,272],"comparison":[145],"additional":[147],"baselines,":[148],"larger":[150],"YOLOv8s-seg":[151],"YOLO11s-seg":[153],"models":[154],"achieve":[155],"values":[158],"0.69161":[160],"0.69434,":[162],"respectively,":[163],"literature-guided":[166],"reimplementation":[167],"Enhanced":[169],"YOLO11n-Seg":[170],"achieves":[171,279],"0.67840":[172],"under":[173],"comparable":[175],"computational":[177],"budget.":[178],"On":[179,266],"untouched":[181],"161-image":[182],"official":[183],"test":[184],"set,":[185],"primary":[187],"results,":[190],"reported":[191],"as":[192],"mean":[194,222],"deviation":[197],"across":[198],"all":[199],"rather":[202],"than":[203],"best-performing":[205],"run,":[206,274],"are":[207,300],"\\(0.6529\\pm":[208],"0.0016\\)":[209,214],"\\(0.6782\\pm":[213],"model,":[218],"corresponding":[219],"gain":[223],"0.0252":[225],"paired":[228],"95%":[229],"confidence":[230],"interval":[231],"[0.0227,":[233],"0.0277].":[234],"Among":[235],"successfully":[236],"matched":[237],"instances":[238],"IoU":[241,246],"\\(\\ge":[242],"0.5\\)":[243],",":[244,254],"Boundary":[245,256],"\\(0.612\\pm":[249],"0.004\\)":[250],"\\(0.651\\pm":[252],"0.003\\)":[253,261],"F-score":[257],"\\(0.744\\pm":[260],"\\(0.779\\pm":[263],"0.002\\)":[264],"same":[268],"development":[273],"parameter/FLOP-matched":[276],"convolutional":[277],"control":[278],"0.66530,":[284],"compared":[285],"0.67007":[287],"CMPRD.":[289],"The":[290],"effects":[291],"spatial":[293],"overall":[297],"mask-loss":[298],"scaling":[299],"not":[301],"isolated,":[302],"cross-dataset":[304],"generalization":[305],"unverified.":[307]},"counts_by_year":[],"updated_date":"2026-11-05T12:25:35.769452","created_date":"2026-11-03T00:00:00"}
