{"id":"https://openalex.org/W4311005692","doi":"https://doi.org/10.3390/electronics11233947","title":"Lightweight Multi-Scale Dilated U-Net for Crop Disease Leaf Image Segmentation","display_name":"Lightweight Multi-Scale Dilated U-Net for Crop Disease Leaf Image Segmentation","publication_year":2022,"publication_date":"2022-11-29","ids":{"openalex":"https://openalex.org/W4311005692","doi":"https://doi.org/10.3390/electronics11233947"},"language":"en","primary_location":{"id":"doi:10.3390/electronics11233947","doi":"https://doi.org/10.3390/electronics11233947","is_oa":true,"landing_page_url":"https://doi.org/10.3390/electronics11233947","pdf_url":"https://www.mdpi.com/2079-9292/11/23/3947/pdf?version=1669716514","source":{"id":"https://openalex.org/S4210202905","display_name":"Electronics","issn_l":"2079-9292","issn":["2079-9292"],"is_oa":true,"is_in_doaj":false,"is_core":true,"listed_in":["anvur-scientific","cwts-core","norway-1","poland-100","russia-white-list-2","vabb-shw"],"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":"Electronics","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.mdpi.com/2079-9292/11/23/3947/pdf?version=1669716514","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101461378","display_name":"Cong Xu","orcid":"https://orcid.org/0000-0001-5374-5530","observed_orcids":["https://orcid.org/0000-0001-5374-5530"]},"institutions":[{"id":"https://openalex.org/I4210162994","display_name":"Xijing University","ror":"https://ror.org/05xsjkb63","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210162994"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Cong Xu","raw_affiliation_strings":["School of Electronic Information, Xijing University, Xi\u2019an 710123, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electronic Information, Xijing University, Xi\u2019an 710123, China","institution_ids":["https://openalex.org/I4210162994"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5047290329","display_name":"Chang-Qing Yu","orcid":"https://orcid.org/0000-0003-4712-8784","observed_orcids":["https://orcid.org/0000-0003-4712-8784"]},"institutions":[{"id":"https://openalex.org/I4210162994","display_name":"Xijing University","ror":"https://ror.org/05xsjkb63","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210162994"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Changqing Yu","raw_affiliation_strings":["School of Electronic Information, Xijing University, Xi\u2019an 710123, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electronic Information, Xijing University, Xi\u2019an 710123, China","institution_ids":["https://openalex.org/I4210162994"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5071771834","display_name":"Shanwen Zhang","orcid":"https://orcid.org/0000-0002-4534-5358","observed_orcids":["https://orcid.org/0000-0002-4534-5358"]},"institutions":[{"id":"https://openalex.org/I4210162994","display_name":"Xijing University","ror":"https://ror.org/05xsjkb63","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210162994"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Shanwen Zhang","raw_affiliation_strings":["School of Electronic Information, Xijing University, Xi\u2019an 710123, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electronic Information, Xijing University, Xi\u2019an 710123, China","institution_ids":["https://openalex.org/I4210162994"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5071771834"],"corresponding_institution_ids":["https://openalex.org/I4210162994"],"apc_list":{"value":2000,"currency":"CHF","value_usd":2094},"apc_paid":{"value":2000,"currency":"CHF","value_usd":2094},"fwci":3.2705,"has_fulltext":true,"cited_by_count":34,"citation_normalized_percentile":{"value":0.92727736,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":"11","issue":"23","first_page":"3947","last_page":"3947"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10616","display_name":"Smart Agriculture and AI","score":0.9955999851226807,"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":0.9955999851226807,"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":0.003700000001117587,"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/T10052","display_name":"Medical Image Segmentation Techniques","score":0.00019999999494757503,"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/lightweight-u-net","display_name":"lightweight U-Net","score":0.7300000190734863},{"id":"https://openalex.org/keywords/multi-scale-dilated-convolution","display_name":"multi-scale dilated convolution","score":0.9290000200271606},{"id":"https://openalex.org/keywords/skip-connections","display_name":"skip connections","score":0.6850000023841858},{"id":"https://openalex.org/keywords/feature-fusion","display_name":"feature fusion","score":0.6290000081062317},{"id":"https://openalex.org/keywords/computational-efficiency","display_name":"computational efficiency","score":0.527999997138977},{"id":"https://openalex.org/keywords/plant-disease-detection","display_name":"plant disease detection","score":0.6349999904632568},{"id":"https://openalex.org/keywords/speckle-noise-robustness","display_name":"speckle noise robustness","score":0.48899999260902405}],"concepts":[{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.6878865957260132},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6195317506790161},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6104387044906616},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5880299806594849},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.584887683391571},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.5532233715057373},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5448647737503052},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.5347503423690796},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.5179885625839233},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.45886537432670593},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.4305873513221741},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.41781190037727356},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.400684118270874},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2360842525959015},{"id":"https://openalex.org/C58640448","wikidata":"https://www.wikidata.org/wiki/Q42515","display_name":"Cartography","level":1,"score":0.08709266781806946},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.3390/electronics11233947","doi":"https://doi.org/10.3390/electronics11233947","is_oa":true,"landing_page_url":"https://doi.org/10.3390/electronics11233947","pdf_url":"https://www.mdpi.com/2079-9292/11/23/3947/pdf?version=1669716514","source":{"id":"https://openalex.org/S4210202905","display_name":"Electronics","issn_l":"2079-9292","issn":["2079-9292"],"is_oa":true,"is_in_doaj":false,"is_core":true,"listed_in":["anvur-scientific","cwts-core","norway-1","poland-100","russia-white-list-2","vabb-shw"],"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":"Electronics","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:32b751c51ae045f5b7d08c5a0154e62a","doi":null,"is_oa":true,"landing_page_url":"https://doaj.org/article/32b751c51ae045f5b7d08c5a0154e62a","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,"listed_in":[],"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":"Electronics, Vol 11, Iss 3947, p 3947 (2022)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.3390/electronics11233947","doi":"https://doi.org/10.3390/electronics11233947","is_oa":true,"landing_page_url":"https://doi.org/10.3390/electronics11233947","pdf_url":"https://www.mdpi.com/2079-9292/11/23/3947/pdf?version=1669716514","source":{"id":"https://openalex.org/S4210202905","display_name":"Electronics","issn_l":"2079-9292","issn":["2079-9292"],"is_oa":true,"is_in_doaj":false,"is_core":true,"listed_in":["anvur-scientific","cwts-core","norway-1","poland-100","russia-white-list-2","vabb-shw"],"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":"Electronics","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/2","score":0.5666999816894531,"display_name":"Zero hunger"}],"study_designs":[],"awards":[{"id":"https://openalex.org/G7915789691","display_name":null,"funder_award_id":"62172338","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8711467752","display_name":"\u57fa\u4e8e\u6df1\u5ea6\u5b66\u4e60\u4e0e\u77e5\u8bc6\u56fe\u8c31\u878d\u5408\u7684\u836f\u7269\u76f8\u4e92\u4f5c\u7528\u9884\u6d4b\u65b9\u6cd5\u7814\u7a76","funder_award_id":"62072378","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/W4311005692.pdf","grobid_xml":"https://content.openalex.org/works/W4311005692.grobid-xml"},"referenced_works_count":26,"referenced_works":["https://openalex.org/W2800213863","https://openalex.org/W2944139570","https://openalex.org/W2963392702","https://openalex.org/W2998066056","https://openalex.org/W3014304846","https://openalex.org/W3082730580","https://openalex.org/W3088208717","https://openalex.org/W3092612188","https://openalex.org/W3107236857","https://openalex.org/W3130521908","https://openalex.org/W3143422447","https://openalex.org/W3160038630","https://openalex.org/W3164934093","https://openalex.org/W3165461249","https://openalex.org/W3178817528","https://openalex.org/W3180998648","https://openalex.org/W3199625624","https://openalex.org/W3201758663","https://openalex.org/W3214847588","https://openalex.org/W4210950978","https://openalex.org/W4220836737","https://openalex.org/W4224229630","https://openalex.org/W4226080951","https://openalex.org/W4281382409","https://openalex.org/W4295919178","https://openalex.org/W4307648357"],"related_works":["https://openalex.org/W4313420555","https://openalex.org/W4386525045","https://openalex.org/W7161480055","https://openalex.org/W7170094258","https://openalex.org/W4415399483","https://openalex.org/W7204938681","https://openalex.org/W7161961087","https://openalex.org/W4415736531","https://openalex.org/W7133329841","https://openalex.org/W4392653220"],"abstract_inverted_index":{"Crop":[0],"disease":[1,10,12,16,181,194],"leaf":[2,49,182,195],"image":[3,183],"segmentation":[4,44],"(CDLIS)":[5],"is":[6,37,72,77,111,139,161],"the":[7,42,85,91,99,103,107,115,122,127,133,148,156,164,170,187],"premise":[8],"of":[9,46,63,79,121,135,137,147,159,200],"detection,":[11],"type":[13],"recognition":[14],"and":[15,24,60,81,98,106,118,130,151,155,172],"degree":[17],"evaluation.":[18],"Various":[19],"convolutional":[20],"neural":[21],"networks":[22],"(CNN)":[23],"their":[25,34],"modified":[26],"models":[27],"have":[28],"been":[29],"provided":[30],"for":[31,74],"CDLIS,":[32],"but":[33],"training":[35],"time":[36],"very":[38],"long.":[39],"Aiming":[40],"at":[41],"low":[43],"accuracy":[45,199],"various":[47],"diseased":[48],"images":[50,196],"caused":[51],"by":[52,141,163],"different":[53],"sizes,":[54],"colors,":[55],"shapes,":[56],"blurred":[57],"speckle":[58],"edges":[59],"complex":[61],"backgrounds":[62],"traditional":[64],"U-Net,":[65,132],"a":[66,95,144,179],"lightweight":[67],"multi-scale":[68,88,131],"extended":[69,89],"U-Net":[70,129,160],"(LWMSDU-Net)":[71],"constructed":[73],"CDLIS.":[75],"It":[76],"composed":[78],"encoding":[80,104],"decoding":[82,92,109],"sub-networks.":[83],"Encoding":[84],"sub-network":[86,93],"adopts":[87,94],"convolution,":[90],"deconvolution":[96],"model,":[97],"residual":[100,165],"connection":[101,158],"between":[102],"module":[105,110],"corresponding":[108],"employed":[112],"to":[113,168],"fuse":[114],"shallow":[116],"features":[117,120],"deep":[119],"input":[123],"image.":[124],"Compared":[125],"with":[126,143,197],"classical":[128],"number":[134,146],"layers":[136],"LWMSDU-Net":[138],"decreased":[140],"1":[142],"small":[145],"trainable":[149],"parameters":[150],"less":[152],"computational":[153],"complexity,":[154],"skip":[157],"replaced":[162],"path":[166],"(Respath)":[167],"connect":[169],"encoder":[171],"decoder":[173],"before":[174],"concatenating.":[175],"Experimental":[176],"results":[177],"on":[178],"crop":[180,193],"dataset":[184],"demonstrate":[185],"that":[186],"proposed":[188],"method":[189],"can":[190],"effectively":[191],"segment":[192],"an":[198],"92.17%.":[201]},"counts_by_year":[{"year":2026,"cited_by_count":9},{"year":2025,"cited_by_count":10},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":11}],"updated_date":"2026-11-05T12:25:35.769452","created_date":"2022-12-22T00:00:00"}
