{"id":"https://openalex.org/W4409781262","doi":"https://doi.org/10.32604/cmc.2025.062010","title":"Plant Disease Detection and Classification Using Hybrid Model Based on Convolutional Auto Encoder and Convolutional Neural Network","display_name":"Plant Disease Detection and Classification Using Hybrid Model Based on Convolutional Auto Encoder and Convolutional Neural Network","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4409781262","doi":"https://doi.org/10.32604/cmc.2025.062010"},"language":"en","primary_location":{"id":"doi:10.32604/cmc.2025.062010","is_oa":true,"landing_page_url":"https://doi.org/10.32604/cmc.2025.062010","pdf_url":null,"source":{"id":"https://openalex.org/S4210191605","display_name":"Computers, materials & continua/Computers, materials & continua (Print)","issn_l":"1546-2218","issn":["1546-2218","1546-2226"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computers, Materials & Continua","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://doi.org/10.32604/cmc.2025.062010","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5102880705","display_name":"Tajinder Kumar","orcid":"https://orcid.org/0000-0002-7079-7065"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Tajinder Kumar","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112104820","display_name":"Sarbjit Kaur","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sarbjit Kaur","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5061246696","display_name":"Purushottam Sharma","orcid":"https://orcid.org/0000-0002-8037-7152"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Purushottam Sharma","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100711636","display_name":"Ankita Chhikara","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ankita Chhikara","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5027459275","display_name":"Xiaochun Cheng","orcid":"https://orcid.org/0000-0003-0371-9646"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xiaochun Cheng","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5038932015","display_name":"Sachin Lalar","orcid":"https://orcid.org/0000-0002-0329-9576"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sachin Lalar","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5007119460","display_name":"Vikram Verma","orcid":"https://orcid.org/0000-0002-5162-5495"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Vikram Verma","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5102880705"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":5.7848,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.94957332,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":91,"max":100},"biblio":{"volume":"83","issue":"3","first_page":"5219","last_page":"5234"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10616","display_name":"Smart Agriculture and AI","score":0.8190000057220459,"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":0.8190000057220459,"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/T13535","display_name":"Wireless Sensor Networks and IoT","score":0.743399977684021,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems 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/convolutional-neural-network","display_name":"Convolutional neural network","score":0.8232883214950562},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5814188718795776},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5448423027992249},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5402870178222656},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.45381492376327515}],"concepts":[{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.8232883214950562},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5814188718795776},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5448423027992249},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5402870178222656},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.45381492376327515},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.32604/cmc.2025.062010","is_oa":true,"landing_page_url":"https://doi.org/10.32604/cmc.2025.062010","pdf_url":null,"source":{"id":"https://openalex.org/S4210191605","display_name":"Computers, materials & continua/Computers, materials & continua (Print)","issn_l":"1546-2218","issn":["1546-2218","1546-2226"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computers, Materials & Continua","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.32604/cmc.2025.062010","is_oa":true,"landing_page_url":"https://doi.org/10.32604/cmc.2025.062010","pdf_url":null,"source":{"id":"https://openalex.org/S4210191605","display_name":"Computers, materials & continua/Computers, materials & continua (Print)","issn_l":"1546-2218","issn":["1546-2218","1546-2226"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computers, Materials & Continua","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W1963517174","https://openalex.org/W2014408679","https://openalex.org/W2395579298","https://openalex.org/W2914622272","https://openalex.org/W2919115771","https://openalex.org/W3036241636","https://openalex.org/W3043119711","https://openalex.org/W3087481060","https://openalex.org/W3215484246","https://openalex.org/W4205486683","https://openalex.org/W4211112186","https://openalex.org/W4255791811","https://openalex.org/W4289523942","https://openalex.org/W4366827437","https://openalex.org/W4390884570","https://openalex.org/W4391735920","https://openalex.org/W4393210145","https://openalex.org/W4394617142","https://openalex.org/W4395013947","https://openalex.org/W4407504933"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2033914206","https://openalex.org/W2042327336"],"abstract_inverted_index":{"During":[0],"its":[1],"growth":[2],"stage,":[3],"the":[4,23,51,57,76,83,91,136,142,153,175,190,202,223,231,237,243],"plant":[5,47,59,228],"is":[6,18,62,87,112,248],"exposed":[7],"to":[8,49,75,90,97,113,173,226,240],"various":[9],"diseases.":[10],"Detection":[11],"and":[12,33,70,82,141,168,201],"early":[13],"detection":[14],"of":[15,56,85,93,107,147,152,177,197,245],"crop":[16,31],"diseases":[17,229],"a":[19,45,115,132,161,186],"major":[20],"challenge":[21],"in":[22,157,212],"horticulture":[24],"industry.":[25],"Crop":[26],"infections":[27],"can":[28,118],"harm":[29],"total":[30],"yield":[32],"reduce":[34],"farmers\u2019":[35],"income":[36],"if":[37],"not":[38],"identified":[39],"early.":[40],"Today\u2019s":[41],"approved":[42],"method":[43],"involves":[44],"professional":[46],"pathologist":[48],"diagnose":[50,125,174],"disease":[52,79],"by":[53],"visual":[54],"inspection":[55],"afflicted":[58],"leaves.":[60],"This":[61],"an":[63],"excellent":[64],"use":[65],"case":[66],"for":[67,109],"Community":[68],"Assessment":[69],"Treatment":[71],"Services":[72],"(CATS)":[73],"due":[74],"lengthy":[77],"manual":[78,105],"diagnosis":[80],"process":[81],"accuracy":[84,204],"identification":[86,106],"directly":[88],"proportional":[89],"skills":[92],"pathologists.":[94],"An":[95],"alternative":[96],"conventional":[98],"Machine":[99],"Learning":[100],"(ML)":[101],"methods,":[102],"which":[103],"require":[104],"parameters":[108],"exact":[110],"results,":[111],"develop":[114],"prototype":[116],"that":[117],"be":[119],"classified":[120],"without":[121],"pre-processing.":[122],"To":[123,149],"automatically":[124,241],"tomato":[126,178,199,246],"leaf":[127],"disease,":[128],"this":[129,158,213,215],"research":[130],"proposes":[131],"hybrid":[133,216],"model":[134,163],"using":[135],"Convolutional":[137,169],"Auto-Encoders":[138],"(CAE)":[139],"network":[140],"CNN-based":[143],"deep":[144],"learning":[145],"architecture":[146],"DenseNet.":[148],"date,":[150],"none":[151],"modern":[154],"systems":[155],"described":[156],"paper":[159],"have":[160],"combined":[162],"based":[164],"on":[165,185],"DenseNet,":[166],"CAE,":[167],"Neural":[170],"Network":[171],"(CNN)":[172],"ailments":[176,244],"leaves":[179],"automatically.":[180],"The":[181,194],"models":[182],"were":[183],"trained":[184,232],"dataset":[187,195],"obtained":[188],"from":[189],"Plant":[191],"Village":[192],"repository.":[193],"consisted":[196],"9920":[198],"leaves,":[200,247],"model-to-model":[203],"ratio":[205],"was":[206],"98.35%.":[207],"Unlike":[208],"other":[209],"approaches":[210],"discussed":[211],"paper,":[214],"strategy":[217],"requires":[218],"fewer":[219],"training":[220,224,238],"components.":[221],"Therefore,":[222],"time":[225,239],"classify":[227],"with":[230],"algorithm,":[233],"as":[234,236],"well":[235],"detect":[242],"significantly":[249],"reduced.":[250]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}