{"id":"https://openalex.org/W4384700341","doi":"https://doi.org/10.1016/j.heliyon.2023.e18261","title":"Enhancing sugarcane disease classification with ensemble deep learning: A comparative study with transfer learning techniques","display_name":"Enhancing sugarcane disease classification with ensemble deep learning: A comparative study with transfer learning techniques","publication_year":2023,"publication_date":"2023-07-18","ids":{"openalex":"https://openalex.org/W4384700341","doi":"https://doi.org/10.1016/j.heliyon.2023.e18261","pmid":"https://pubmed.ncbi.nlm.nih.gov/37520940","pmcid":"https://www.ncbi.nlm.nih.gov/pmc/articles/10382639"},"language":"en","primary_location":{"id":"doi:10.1016/j.heliyon.2023.e18261","doi":"https://doi.org/10.1016/j.heliyon.2023.e18261","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.heliyon.2023.e18261","pdf_url":"http://www.cell.com/article/S2405844023054695/pdf","source":{"id":"https://openalex.org/S2898612692","display_name":"Heliyon","issn_l":"2405-8440","issn":["2405-8440"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["anvur-class-a","anvur-scientific","cwts-core","doaj","dongbi-c","ki-jl-1","norway-1","poland-40","vabb-shw"],"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"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":"Heliyon","raw_type":"journal-article"},"volume":null,"type":"article","is_traditional":true,"indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"http://www.cell.com/article/S2405844023054695/pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5084715814","display_name":"Swapnil Dadabhau Daphal","orcid":"https://orcid.org/0000-0003-2827-9018","observed_orcids":["https://orcid.org/0000-0003-2827-9018"]},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Swapnil Dadabhau Daphal","raw_affiliation_strings":["Department of E&TC Engineering, G. H. Raisoni College of Engineering & Management, Wagholi, Pune, 412207, Maharashtra, India"],"raw_orcid":"https://orcid.org/0000-0003-2827-9018","affiliations":[{"raw_affiliation_string":"Department of E&TC Engineering, G. H. Raisoni College of Engineering & Management, Wagholi, Pune, 412207, Maharashtra, India","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5032082506","display_name":"Sanjay Mahadev Koli","orcid":"https://orcid.org/0000-0001-5401-959X","observed_orcids":["https://orcid.org/0000-0001-5401-959X"]},"institutions":[{"id":"https://openalex.org/I4403386594","display_name":"Ajeenkya DY Patil University","ror":"https://ror.org/02v423c65","country_code":"IN","type":"education","lineage":["https://openalex.org/I4403386594"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Sanjay M. Koli","raw_affiliation_strings":["Department of E&TC Engineering, Ajeenkya DY Patil School of Engineering, Charholi Bk., Pune, 412105, Maharashtra, India","Departement of E&TC Engineering, Ajeenkya DY Patil School of Engineering, Charholi Bk., Pune, 412105, Maharashtra, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of E&TC Engineering, Ajeenkya DY Patil School of Engineering, Charholi Bk., Pune, 412105, Maharashtra, India","institution_ids":["https://openalex.org/I4403386594"]},{"raw_affiliation_string":"Departement of E&TC Engineering, Ajeenkya DY Patil School of Engineering, Charholi Bk., Pune, 412105, Maharashtra, India","institution_ids":["https://openalex.org/I4403386594"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5084715814"],"corresponding_institution_ids":[],"apc_list":{"value":2100,"currency":"USD","value_usd":2100},"apc_paid":{"value":2100,"currency":"USD","value_usd":2100},"fwci":10.3863,"has_fulltext":true,"cited_by_count":76,"citation_normalized_percentile":{"value":0.99222017,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":88,"max":100},"biblio":{"volume":"9","issue":"8","first_page":"e18261","last_page":"e18261"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10616","display_name":"Smart Agriculture and AI","score":0.9994999766349792,"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":0.9994999766349792,"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":0.00019999999494757503,"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"}},{"id":"https://openalex.org/T10494","display_name":"Plant Virus Research Studies","score":0.0,"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/plant-disease-detection","display_name":"plant disease detection","score":0.7870000004768372},{"id":"https://openalex.org/keywords/ensemble-deep-learning","display_name":"ensemble deep learning","score":0.9760000109672546},{"id":"https://openalex.org/keywords/transfer-learning","display_name":"transfer learning","score":0.7929999828338623},{"id":"https://openalex.org/keywords/spatial-attention","display_name":"spatial attention","score":0.7620000243186951},{"id":"https://openalex.org/keywords/mobilenetv2","display_name":"MobileNetV2","score":0.9440000057220459},{"id":"https://openalex.org/keywords/agricultural-image-classification","display_name":"agricultural image classification","score":0.5899999737739563}],"concepts":[{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.8546172380447388},{"id":"https://openalex.org/C45942800","wikidata":"https://www.wikidata.org/wiki/Q245652","display_name":"Ensemble learning","level":2,"score":0.7837352752685547},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.7040949463844299},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6989249587059021},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6734331250190735},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.6173064708709717},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5932977199554443},{"id":"https://openalex.org/C134121241","wikidata":"https://www.wikidata.org/wiki/Q899301","display_name":"Yield (engineering)","level":2,"score":0.412829726934433},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.37475764751434326},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.22896668314933777},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C191897082","wikidata":"https://www.wikidata.org/wiki/Q11467","display_name":"Metallurgy","level":1,"score":0.0},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1016/j.heliyon.2023.e18261","doi":"https://doi.org/10.1016/j.heliyon.2023.e18261","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.heliyon.2023.e18261","pdf_url":"http://www.cell.com/article/S2405844023054695/pdf","source":{"id":"https://openalex.org/S2898612692","display_name":"Heliyon","issn_l":"2405-8440","issn":["2405-8440"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["anvur-class-a","anvur-scientific","cwts-core","doaj","dongbi-c","ki-jl-1","norway-1","poland-40","vabb-shw"],"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"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":"Heliyon","raw_type":"journal-article"},{"id":"pmh:oai:pubmedcentral.nih.gov:10382639","doi":null,"is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/10382639","pdf_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC10382639/pdf/main.pdf","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,"listed_in":[],"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-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Heliyon","raw_type":"Text"},{"id":"pmid:37520940","doi":null,"is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/37520940","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,"listed_in":[],"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":"Heliyon","raw_type":"Journal Article"},{"id":"pmh:oai:doaj.org/article:b0390c971d024bf88274accb2abd5b58","doi":null,"is_oa":true,"landing_page_url":"https://doaj.org/article/b0390c971d024bf88274accb2abd5b58","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":"Heliyon, Vol 9, Iss 8, Pp e18261- (2023)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1016/j.heliyon.2023.e18261","doi":"https://doi.org/10.1016/j.heliyon.2023.e18261","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.heliyon.2023.e18261","pdf_url":"http://www.cell.com/article/S2405844023054695/pdf","source":{"id":"https://openalex.org/S2898612692","display_name":"Heliyon","issn_l":"2405-8440","issn":["2405-8440"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["anvur-class-a","anvur-scientific","cwts-core","doaj","dongbi-c","ki-jl-1","norway-1","poland-40","vabb-shw"],"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"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":"Heliyon","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/2","display_name":"Zero hunger","score":0.875}],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4384700341.pdf","grobid_xml":"https://content.openalex.org/works/W4384700341.grobid-xml"},"referenced_works_count":47,"referenced_works":["https://openalex.org/W1530690000","https://openalex.org/W2194775991","https://openalex.org/W2738170702","https://openalex.org/W2791110299","https://openalex.org/W2886876600","https://openalex.org/W2963163009","https://openalex.org/W2979617155","https://openalex.org/W3028098469","https://openalex.org/W3033196717","https://openalex.org/W3082076807","https://openalex.org/W3093991637","https://openalex.org/W3143167896","https://openalex.org/W3153854354","https://openalex.org/W3154181045","https://openalex.org/W3177525997","https://openalex.org/W3178340391","https://openalex.org/W3190789542","https://openalex.org/W3198061946","https://openalex.org/W3201606813","https://openalex.org/W3205898796","https://openalex.org/W3206899080","https://openalex.org/W4200249297","https://openalex.org/W4205467977","https://openalex.org/W4205549623","https://openalex.org/W4206553819","https://openalex.org/W4206618551","https://openalex.org/W4206832965","https://openalex.org/W4210891047","https://openalex.org/W4210894089","https://openalex.org/W4210940958","https://openalex.org/W4225726725","https://openalex.org/W4226114915","https://openalex.org/W4226177094","https://openalex.org/W4226546757","https://openalex.org/W4229444636","https://openalex.org/W4234950299","https://openalex.org/W4243433306","https://openalex.org/W4249343796","https://openalex.org/W4255556797","https://openalex.org/W4280567993","https://openalex.org/W4280572123","https://openalex.org/W4285122401","https://openalex.org/W4285244386","https://openalex.org/W4285266756","https://openalex.org/W4319718472","https://openalex.org/W4328007200","https://openalex.org/W6789939941"],"related_works":["https://openalex.org/W7155995440","https://openalex.org/W4210894089","https://openalex.org/W4409310705","https://openalex.org/W4404817224","https://openalex.org/W7160661725","https://openalex.org/W7130707148","https://openalex.org/W4407221167","https://openalex.org/W4408400119","https://openalex.org/W4410259655","https://openalex.org/W4409427149"],"abstract_inverted_index":{"Deep":[0],"learning":[1,52,58,113],"practices":[2],"in":[3],"the":[4,13,31,35,45,48,89,123],"agriculture":[5],"sector":[6],"can":[7],"address":[8],"many":[9],"challenges":[10],"faced":[11],"by":[12],"farmers":[14],"such":[15],"as":[16],"disease":[17,28],"detection,":[18],"yield":[19],"estimation,":[20,23],"soil":[21],"profile":[22],"etc.":[24],"In":[25],"this":[26,93],"paper,":[27],"classification":[29],"for":[30],"sugarcane":[32,83],"plant":[33],"and":[34,54,137],"experimentation":[36],"involved":[37],"thereby":[38],"is":[39,86,107],"thoroughly":[40],"discussed.":[41],"Experimental":[42],"results":[43],"include":[44],"performances":[46],"of":[47,65,82,102,119,126,141],"well-known":[49],"existing":[50],"transfer":[51,112],"techniques":[53],"proposed":[55],"ensemble":[56,64,129],"deep":[57],"based":[59],"architecture":[60],"that":[61,109],"incorporates":[62],"stack":[63],"two":[66],"networks":[67],"with":[68,99,122,134,138],"one":[69],"having":[70],"level-wise":[71],"spatial":[72],"attention":[73],"helping":[74],"to":[75,88,132],"provide":[76],"better":[77],"generalization.":[78],"A":[79],"Self-created":[80],"database":[81],"leaf":[84],"diseases":[85],"introduced":[87],"research":[90],"community":[91],"through":[92],"paper.":[94],"It":[95],"involves":[96],"5":[97],"categories":[98],"a":[100],"total":[101],"2569":[103],"images.":[104],"Here,":[105],"it":[106],"observed":[108],"best":[110],"performing":[111],"method,":[114],"MobileNet-V2":[115],"shows":[116],"an":[117],"accuracy":[118],"around":[120],"84%":[121],"lowest":[124],"number":[125,140],"parameters":[127],"whereas":[128],"model":[130],"reaching":[131],"86.53%":[133],"less":[135],"epochs":[136],"acceptable":[139],"parameters.":[142]},"counts_by_year":[{"year":2026,"cited_by_count":27},{"year":2025,"cited_by_count":23},{"year":2024,"cited_by_count":25},{"year":2023,"cited_by_count":1}],"updated_date":"2026-11-12T12:28:57.059296","created_date":"2023-07-20T00:00:00"}
