{"id":"https://openalex.org/W4285270699","doi":"https://doi.org/10.1109/access.2022.3187825","title":"A Method of Crop Seedling Plant Segmentation on Edge Information Fusion Model","display_name":"A Method of Crop Seedling Plant Segmentation on Edge Information Fusion Model","publication_year":2022,"publication_date":"2022-01-01","ids":{"openalex":"https://openalex.org/W4285270699","doi":"https://doi.org/10.1109/access.2022.3187825"},"language":"en","primary_location":{"id":"doi:10.1109/access.2022.3187825","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2022.3187825","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/09812623.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/09812623.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5102821246","display_name":"Xin Zuo","orcid":"https://orcid.org/0000-0002-9707-9303"},"institutions":[{"id":"https://openalex.org/I4210087731","display_name":"Guizhou Education University","ror":"https://ror.org/002x6f380","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210087731"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xin Zuo","raw_affiliation_strings":["School of Mathematics and Big Data, Guizhou Education University, Guiyang, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Mathematics and Big Data, Guizhou Education University, Guiyang, China","institution_ids":["https://openalex.org/I4210087731"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5058323321","display_name":"Hong Lin","orcid":"https://orcid.org/0000-0003-1827-5507"},"institutions":[{"id":"https://openalex.org/I4210087731","display_name":"Guizhou Education University","ror":"https://ror.org/002x6f380","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210087731"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hong Lin","raw_affiliation_strings":["Big Data Science and Intelligent Engineering Research Institute, Guizhou Education University, Guiyang, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Big Data Science and Intelligent Engineering Research Institute, Guizhou Education University, Guiyang, China","institution_ids":["https://openalex.org/I4210087731"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100391405","display_name":"Dong Wang","orcid":"https://orcid.org/0000-0001-6224-2265"},"institutions":[{"id":"https://openalex.org/I4210087731","display_name":"Guizhou Education University","ror":"https://ror.org/002x6f380","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210087731"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dong Wang","raw_affiliation_strings":["School of Mathematics and Big Data, Guizhou Education University, Guiyang, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Mathematics and Big Data, Guizhou Education University, Guiyang, China","institution_ids":["https://openalex.org/I4210087731"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5073482873","display_name":"Zhongwei Cui","orcid":"https://orcid.org/0000-0001-9549-7440"},"institutions":[{"id":"https://openalex.org/I4210087731","display_name":"Guizhou Education University","ror":"https://ror.org/002x6f380","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210087731"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhongwei Cui","raw_affiliation_strings":["School of Mathematics and Big Data, Guizhou Education University, Guiyang, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Mathematics and Big Data, Guizhou Education University, Guiyang, China","institution_ids":["https://openalex.org/I4210087731"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I4210087731"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":1.0602,"has_fulltext":true,"cited_by_count":12,"citation_normalized_percentile":{"value":0.75187993,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":97,"max":98},"biblio":{"volume":"10","issue":null,"first_page":"95281","last_page":"95293"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T14257","display_name":"Advanced Measurement and Detection Methods","score":0.9894000291824341,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T14257","display_name":"Advanced Measurement and Detection Methods","score":0.9894000291824341,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic 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/T13890","display_name":"Remote Sensing and Land Use","score":0.9890000224113464,"subfield":{"id":"https://openalex.org/subfields/1902","display_name":"Atmospheric Science"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T13832","display_name":"Advanced Decision-Making Techniques","score":0.9847999811172485,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/seedling","display_name":"Seedling","score":0.7322800755500793},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5466135740280151},{"id":"https://openalex.org/keywords/crop","display_name":"Crop","score":0.49141228199005127},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.4695233404636383},{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.4616727828979492},{"id":"https://openalex.org/keywords/information-fusion","display_name":"Information fusion","score":0.42436307668685913},{"id":"https://openalex.org/keywords/agricultural-engineering","display_name":"Agricultural engineering","score":0.35580307245254517},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3158062696456909},{"id":"https://openalex.org/keywords/agronomy","display_name":"Agronomy","score":0.22757747769355774},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.13269886374473572},{"id":"https://openalex.org/keywords/biology","display_name":"Biology","score":0.07791769504547119}],"concepts":[{"id":"https://openalex.org/C2776096895","wikidata":"https://www.wikidata.org/wiki/Q1385709","display_name":"Seedling","level":2,"score":0.7322800755500793},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5466135740280151},{"id":"https://openalex.org/C137580998","wikidata":"https://www.wikidata.org/wiki/Q235352","display_name":"Crop","level":2,"score":0.49141228199005127},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.4695233404636383},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.4616727828979492},{"id":"https://openalex.org/C2982962833","wikidata":"https://www.wikidata.org/wiki/Q17092450","display_name":"Information fusion","level":2,"score":0.42436307668685913},{"id":"https://openalex.org/C88463610","wikidata":"https://www.wikidata.org/wiki/Q194118","display_name":"Agricultural engineering","level":1,"score":0.35580307245254517},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3158062696456909},{"id":"https://openalex.org/C6557445","wikidata":"https://www.wikidata.org/wiki/Q173113","display_name":"Agronomy","level":1,"score":0.22757747769355774},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.13269886374473572},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.07791769504547119}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2022.3187825","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2022.3187825","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/09812623.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:d04c9657d91647b683ed62e2e373ae57","is_oa":true,"landing_page_url":"https://doaj.org/article/d04c9657d91647b683ed62e2e373ae57","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":"IEEE Access, Vol 10, Pp 95281-95293 (2022)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2022.3187825","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2022.3187825","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/09812623.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/15","score":0.4399999976158142,"display_name":"Life in Land"}],"awards":[{"id":"https://openalex.org/G2137029343","display_name":null,"funder_award_id":"[2021]022","funder_id":"https://openalex.org/F4320326674","funder_display_name":"Department of Education of Guizhou Province"},{"id":"https://openalex.org/G2806078944","display_name":null,"funder_award_id":"QianJiaoHeKY[2021]022","funder_id":"https://openalex.org/F4320318381","funder_display_name":"Guizhou Education University"},{"id":"https://openalex.org/G4504556064","display_name":null,"funder_award_id":"QianJiaoHeKY[2022]293","funder_id":"https://openalex.org/F4320335952","funder_display_name":"Guizhou Education Department Youth Science and Technology Talents Growth Project"}],"funders":[{"id":"https://openalex.org/F4320318381","display_name":"Guizhou Education University","ror":"https://ror.org/002x6f380"},{"id":"https://openalex.org/F4320326674","display_name":"Department of Education of Guizhou Province","ror":null},{"id":"https://openalex.org/F4320335952","display_name":"Guizhou Education Department Youth Science and Technology Talents Growth Project","ror":null}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4285270699.pdf","grobid_xml":"https://content.openalex.org/works/W4285270699.grobid-xml"},"referenced_works_count":10,"referenced_works":["https://openalex.org/W2969364300","https://openalex.org/W2995877391","https://openalex.org/W3091927242","https://openalex.org/W3128670286","https://openalex.org/W3166424296","https://openalex.org/W3167175873","https://openalex.org/W3187978113","https://openalex.org/W4200459217","https://openalex.org/W4213302030","https://openalex.org/W4361976226"],"related_works":["https://openalex.org/W2388922981","https://openalex.org/W2376588297","https://openalex.org/W2043993394","https://openalex.org/W2379020407","https://openalex.org/W2366809278","https://openalex.org/W2111376716","https://openalex.org/W2257276718","https://openalex.org/W2378658865","https://openalex.org/W2355792773","https://openalex.org/W2146559394"],"abstract_inverted_index":{"Automatic":[0],"segmentation":[1,88,281],"of":[2,17,39,44,76,98,106,191,232,298,307],"plant":[3,10,87,118],"images":[4],"is":[5,14,57,104,162,171],"a":[6,84,132,158,217],"hot":[7],"issue":[8],"in":[9,49,69,173,268,289,292],"phenotyping":[11],"research.":[12],"It":[13],"also":[15],"one":[16],"the":[18,34,50,93,107,112,117,125,138,142,147,174,189,194,250,255,266,280,285,293,299,303,308,312],"core":[19],"technologies":[20],"for":[21,164,200],"applications":[22],"such":[23],"as":[24],"crop":[25,67,85],"growth":[26],"process":[27],"monitoring":[28],"and":[29,37,42,46,53,72,79,95,146,154,183,212,221,240,259,273],"pest":[30],"identification.":[31],"Due":[32],"to":[33,59,64,115,130,181,187,207,228,236,284],"different":[35,233],"scales":[36],"sizes":[38],"fruits,":[40],"branches":[41],"leaves":[43],"fruit":[45],"vegetable":[47],"plants":[48],"natural":[51,70],"environment,":[52],"irregular":[54],"edges,":[55],"it":[56],"difficult":[58],"accurately":[60,65],"segment.":[61],"In":[62],"order":[63],"segment":[66],"seedlings":[68],"environment":[71],"realize":[73],"automatic":[74],"measurement":[75],"seedling":[77,86,301],"location":[78],"phenotype,":[80],"this":[81,269],"paper":[82,270],"proposes":[83],"network":[89,103,114,145,166,170,178,196,252],"model":[90],"that":[91,248],"fuses":[92,137],"semantic":[94,214],"edge":[96,119,148],"information":[97,120,192,211],"target":[99],"regions.":[100],"The":[101,168,176,244],"backbone":[102,113,144],"composed":[105],"UNET":[108,143],"network,":[109],"which":[110,136,276],"guides":[111],"perceive":[116],"when":[121],"extracting":[122],"features;":[123],"uses":[124,179,197],"spatial":[126,224],"hole":[127,218],"feature":[128,133,155,230],"pyramid":[129,225],"build":[131],"fusion":[134,156],"module,":[135],"features":[139,186,239],"extracted":[140],"by":[141,264],"perception":[149],"module.":[150],"Combining":[151],"edge-aware":[152],"loss":[153,160],"loss,":[157],"joint":[159],"function":[161],"constructed":[163],"overall":[165],"optimization.":[167],"encoder-decoder":[169],"referenced":[172],"study.":[175],"encoding":[177,220],"densenet":[180],"reuse":[182],"fuse":[184,208],"multi-layer":[185],"improve":[188],"way":[190],"transmission;":[193],"decoding":[195,222],"transposed":[198],"convolution":[199],"upsampling,":[201],"combined":[202],"with":[203,319],"layer":[204],"jump":[205],"connections":[206],"shallow":[209],"detail":[210],"deep":[213],"information;":[215],"add":[216],"between":[219],"Atrous":[223],"pooling":[226],"(ASPP)":[227],"extract":[229],"maps":[231],"receptive":[234],"fields":[235],"integrate":[237],"multi-scale":[238],"aggregate":[241],"contextual":[242],"information.":[243],"experimental":[245],"results":[246,282],"show":[247],"under":[249],"same":[251],"training":[253,294],"parameters,":[254],"average":[256,260,304],"cross-merging":[257],"rate":[258,262],"recall":[261],"obtained":[263],"testing":[265],"method":[267,310],"are":[271,277],"58.13%":[272],"64.72%,":[274],"respectively,":[275],"better":[278],"than":[279],"corresponding":[283],"manually":[286],"labeled":[287],"samples;":[288],"addition,":[290],"adding":[291],"samples":[295],"After":[296],"10%":[297],"outdoor":[300,313],"images,":[302],"pixel":[305],"accuracy":[306],"proposed":[309],"on":[311],"test":[314],"set":[315],"can":[316],"reach":[317],"90.54%,":[318],"good":[320],"generalization":[321],"ability.":[322]},"counts_by_year":[{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":4}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
