{"id":"https://openalex.org/W4400810823","doi":"https://doi.org/10.1109/isie54533.2024.10595796","title":"S<sup>2</sup>MD<sup>2</sup>: A Method for Semi-Supervised Maize Leaf Disease Detection","display_name":"S<sup>2</sup>MD<sup>2</sup>: A Method for Semi-Supervised Maize Leaf Disease Detection","publication_year":2024,"publication_date":"2024-06-18","ids":{"openalex":"https://openalex.org/W4400810823","doi":"https://doi.org/10.1109/isie54533.2024.10595796"},"language":"en","primary_location":{"id":"doi:10.1109/isie54533.2024.10595796","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/isie54533.2024.10595796","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE 33rd International Symposium on Industrial Electronics (ISIE)","raw_type":"proceedings-article"},"type":"article","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/A5101779755","display_name":"Chengcheng Chen","orcid":"https://orcid.org/0000-0002-6015-5413"},"institutions":[{"id":"https://openalex.org/I125904092","display_name":"Shenyang Aerospace University","ror":"https://ror.org/02423gm04","country_code":"CN","type":"education","lineage":["https://openalex.org/I125904092"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Chengcheng Chen","raw_affiliation_strings":["Shenyang Aerospace University,School of Computer Science,China"],"affiliations":[{"raw_affiliation_string":"Shenyang Aerospace University,School of Computer Science,China","institution_ids":["https://openalex.org/I125904092"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100457936","display_name":"Weijia Zhang","orcid":"https://orcid.org/0000-0001-6928-0416"},"institutions":[{"id":"https://openalex.org/I125904092","display_name":"Shenyang Aerospace University","ror":"https://ror.org/02423gm04","country_code":"CN","type":"education","lineage":["https://openalex.org/I125904092"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weijia Zhang","raw_affiliation_strings":["Shenyang Aerospace University,School of Computer Science,China"],"affiliations":[{"raw_affiliation_string":"Shenyang Aerospace University,School of Computer Science,China","institution_ids":["https://openalex.org/I125904092"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5084140502","display_name":"Ronghao Fu","orcid":"https://orcid.org/0000-0002-0751-224X"},"institutions":[{"id":"https://openalex.org/I194450716","display_name":"Jilin University","ror":"https://ror.org/00js3aw79","country_code":"CN","type":"education","lineage":["https://openalex.org/I194450716"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ronghao Fu","raw_affiliation_strings":["Jilin University,College of Computer Science and Technology,China"],"affiliations":[{"raw_affiliation_string":"Jilin University,College of Computer Science and Technology,China","institution_ids":["https://openalex.org/I194450716"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5055380186","display_name":"Tairan Wang","orcid":"https://orcid.org/0000-0002-0220-6059"},"institutions":[{"id":"https://openalex.org/I125904092","display_name":"Shenyang Aerospace University","ror":"https://ror.org/02423gm04","country_code":"CN","type":"education","lineage":["https://openalex.org/I125904092"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tairan Wang","raw_affiliation_strings":["Shenyang Aerospace University,School of Computer Science,China"],"affiliations":[{"raw_affiliation_string":"Shenyang Aerospace University,School of Computer Science,China","institution_ids":["https://openalex.org/I125904092"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5066052286","display_name":"Tiantian Pang","orcid":null},"institutions":[{"id":"https://openalex.org/I194450716","display_name":"Jilin University","ror":"https://ror.org/00js3aw79","country_code":"CN","type":"education","lineage":["https://openalex.org/I194450716"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tiantian Pang","raw_affiliation_strings":["Jilin University,College of Computer Science and Technology,China"],"affiliations":[{"raw_affiliation_string":"Jilin University,College of Computer Science and Technology,China","institution_ids":["https://openalex.org/I194450716"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5032607111","display_name":"Jiehong Wu","orcid":"https://orcid.org/0000-0002-0851-3009"},"institutions":[{"id":"https://openalex.org/I125904092","display_name":"Shenyang Aerospace University","ror":"https://ror.org/02423gm04","country_code":"CN","type":"education","lineage":["https://openalex.org/I125904092"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiehong Wu","raw_affiliation_strings":["Shenyang Aerospace University,School of Computer Science,China"],"affiliations":[{"raw_affiliation_string":"Shenyang Aerospace University,School of Computer Science,China","institution_ids":["https://openalex.org/I125904092"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102839301","display_name":"Zhiyong Zheng","orcid":"https://orcid.org/0000-0002-6386-5066"},"institutions":[{"id":"https://openalex.org/I125904092","display_name":"Shenyang Aerospace University","ror":"https://ror.org/02423gm04","country_code":"CN","type":"education","lineage":["https://openalex.org/I125904092"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhiyong Zheng","raw_affiliation_strings":["Shenyang Aerospace University,School of Computer Science,China"],"affiliations":[{"raw_affiliation_string":"Shenyang Aerospace University,School of Computer Science,China","institution_ids":["https://openalex.org/I125904092"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5089702415","display_name":"Xianchang Wang","orcid":"https://orcid.org/0000-0001-8775-8188"},"institutions":[{"id":"https://openalex.org/I125904092","display_name":"Shenyang Aerospace University","ror":"https://ror.org/02423gm04","country_code":"CN","type":"education","lineage":["https://openalex.org/I125904092"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xianchang Wang","raw_affiliation_strings":["Shenyang Aerospace University,School of Computer Science,China"],"affiliations":[{"raw_affiliation_string":"Shenyang Aerospace University,School of Computer Science,China","institution_ids":["https://openalex.org/I125904092"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":8,"corresponding_author_ids":["https://openalex.org/A5101779755"],"corresponding_institution_ids":["https://openalex.org/I125904092"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.0617555,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"5","issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10616","display_name":"Smart Agriculture and AI","score":0.9592000246047974,"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":0.9592000246047974,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.3948819041252136},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.37894782423973083}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.3948819041252136},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.37894782423973083}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/isie54533.2024.10595796","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/isie54533.2024.10595796","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE 33rd International Symposium on Industrial Electronics (ISIE)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Zero hunger","id":"https://metadata.un.org/sdg/2","score":0.7599999904632568}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":32,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W1969368146","https://openalex.org/W2018105531","https://openalex.org/W2339460098","https://openalex.org/W2888222694","https://openalex.org/W2905406841","https://openalex.org/W2935842115","https://openalex.org/W2953070460","https://openalex.org/W2966002724","https://openalex.org/W2978426779","https://openalex.org/W3016616248","https://openalex.org/W3021542222","https://openalex.org/W3035160371","https://openalex.org/W3130877874","https://openalex.org/W3130976481","https://openalex.org/W3158527823","https://openalex.org/W3172507542","https://openalex.org/W3175496851","https://openalex.org/W4212774754","https://openalex.org/W4224306206","https://openalex.org/W4243215724","https://openalex.org/W4288325606","https://openalex.org/W4289641133","https://openalex.org/W4309912881","https://openalex.org/W4318561823","https://openalex.org/W4387133400","https://openalex.org/W6703892329","https://openalex.org/W6733814495","https://openalex.org/W6762913911","https://openalex.org/W6773005947","https://openalex.org/W6776778719","https://openalex.org/W6789505266"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2748952813","https://openalex.org/W2935759653","https://openalex.org/W3105167352","https://openalex.org/W54078636","https://openalex.org/W2954470139","https://openalex.org/W1501425562","https://openalex.org/W2902782467","https://openalex.org/W3084825885","https://openalex.org/W2298861036"],"abstract_inverted_index":{"Maize":[0],"leaf":[1,33,55,62,140],"diseases":[2,34,63,77,141],"are":[3,50],"critical":[4],"determinants":[5],"of":[6,14,45,53,60,72,82,95,163,174,185,198,219],"maize":[7,32,54,61,139],"yield":[8],"and":[9,16,30,37,39,97,99,109,124,192],"quality.":[10],"With":[11],"the":[12,68,80,153,166,182,186,199,202,208,228,240],"decrease":[13],"population":[15],"arable":[17],"land":[18],"resources,":[19],"deep":[20,87],"learning-based":[21],"machine":[22],"vision":[23],"methods":[24],"provide":[25],"obvious":[26],"advantages":[27],"in":[28,35,67,189,201],"recognizing":[29],"detecting":[31,138],"precision":[36],"cost,":[38],"it":[40,100],"has":[41],"become":[42],"a":[43,92,134,148,160,171,211,235],"hotspot":[44],"current":[46],"research.":[47],"However,":[48],"there":[49],"many":[51],"types":[52,59],"diseases,":[56],"over":[57],"90":[58],"can":[64],"be":[65],"found":[66],"worldwide.":[69],"The":[70],"diagnosis":[71],"one":[73],"disease":[74,194],"or":[75],"several":[76],"cannot":[78],"fulfill":[79],"needs":[81],"practical":[83],"applications.":[84],"In":[85,129,221],"addition,":[86],"learning":[88,114,144,242],"model":[89,151,167],"training":[90],"requires":[91],"large":[93,172],"amount":[94],"datasets":[96],"label,":[98],"is":[101,126,231,234],"very":[102],"difficult":[103],"to":[104,239],"obtain":[105],"comprehensive":[106],"dataset":[107,205],"samples":[108,123],"labels":[110],"with":[111],"existing":[112],"supervised":[113,241],"methods.":[115],"A":[116],"method":[117,136,209],"that":[118,207],"relies":[119],"on":[120],"limited":[121],"data":[122,230],"label":[125],"desperately":[127],"needed.":[128],"this":[130],"paper,":[131],"we":[132],"propose":[133],"novel":[135],"for":[137,170],"using":[142],"semi-supervised":[143],"techniques,":[145],"which":[146,233],"incorporates":[147],"soft":[149],"teacher":[150],"into":[152],"Faster":[154],"R-CNN":[155],"network":[156],"framework.":[157],"By":[158],"leveraging":[159],"small":[161],"set":[162],"labeled":[164,229],"data,":[165],"generates":[168],"pseudo-labels":[169],"pool":[173],"unlabeled":[175],"data.":[176,220],"This":[177],"innovative":[178],"strategy":[179],"significantly":[180],"enhances":[181],"detection":[183,195,213],"performance":[184,224],"model,":[187],"resulting":[188],"more":[190],"accurate":[191],"reliable":[193],"outcomes.":[196],"Results":[197],"experiment":[200],"PlantVillage":[203],"public":[204],"indicated":[206],"achieved":[210],"superior":[212],"result":[214],"under":[215],"different":[216],"labeling":[217],"percentages":[218],"particular,":[222],"its":[223],"reaches":[225],"57.2%":[226],"when":[227],"50%,":[232],"25.1%":[236],"improvement":[237],"compared":[238],"method.":[243]},"counts_by_year":[],"updated_date":"2025-12-26T23:08:49.675405","created_date":"2025-10-10T00:00:00"}