{"id":"https://openalex.org/W4410449090","doi":"https://doi.org/10.32604/cmc.2025.061995","title":"Enhanced Wheat Disease Detection Using Deep Learning and Explainable AI Techniques","display_name":"Enhanced Wheat Disease Detection Using Deep Learning and Explainable AI Techniques","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4410449090","doi":"https://doi.org/10.32604/cmc.2025.061995"},"language":"en","primary_location":{"id":"doi:10.32604/cmc.2025.061995","is_oa":true,"landing_page_url":"https://doi.org/10.32604/cmc.2025.061995","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.2025.061995","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5117574011","display_name":"Hussam Qushtom","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Hussam Qushtom","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5008566898","display_name":"Ahmad Hasasneh","orcid":"https://orcid.org/0000-0002-5794-928X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ahmad Hasasneh","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5011528836","display_name":"Sari Masri","orcid":"https://orcid.org/0009-0000-1592-2540"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sari Masri","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5117574011"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":7.0906,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.96300879,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":"84","issue":"1","first_page":"1379","last_page":"1395"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10616","display_name":"Smart Agriculture and AI","score":0.9592999815940857,"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":0.9592999815940857,"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/deep-learning","display_name":"Deep learning","score":0.5555974841117859},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5421165227890015},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4801889657974243},{"id":"https://openalex.org/keywords/disease","display_name":"Disease","score":0.4354696273803711},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.21775665879249573},{"id":"https://openalex.org/keywords/internal-medicine","display_name":"Internal medicine","score":0.09488523006439209}],"concepts":[{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5555974841117859},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5421165227890015},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4801889657974243},{"id":"https://openalex.org/C2779134260","wikidata":"https://www.wikidata.org/wiki/Q12136","display_name":"Disease","level":2,"score":0.4354696273803711},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.21775665879249573},{"id":"https://openalex.org/C126322002","wikidata":"https://www.wikidata.org/wiki/Q11180","display_name":"Internal medicine","level":1,"score":0.09488523006439209}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.32604/cmc.2025.061995","is_oa":true,"landing_page_url":"https://doi.org/10.32604/cmc.2025.061995","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.2025.061995","is_oa":true,"landing_page_url":"https://doi.org/10.32604/cmc.2025.061995","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":22,"referenced_works":["https://openalex.org/W2735962203","https://openalex.org/W2955236000","https://openalex.org/W2981116508","https://openalex.org/W3081995103","https://openalex.org/W3174396058","https://openalex.org/W3195133177","https://openalex.org/W3216854021","https://openalex.org/W4220794085","https://openalex.org/W4226048511","https://openalex.org/W4226165565","https://openalex.org/W4285803521","https://openalex.org/W4291753147","https://openalex.org/W4293770138","https://openalex.org/W4307871206","https://openalex.org/W4313443719","https://openalex.org/W4324257920","https://openalex.org/W4361802800","https://openalex.org/W4376645186","https://openalex.org/W4382195690","https://openalex.org/W4394064951","https://openalex.org/W4399199219","https://openalex.org/W4404720546"],"related_works":["https://openalex.org/W2731899572","https://openalex.org/W3215138031","https://openalex.org/W3009238340","https://openalex.org/W4360585206","https://openalex.org/W4321369474","https://openalex.org/W4285208911","https://openalex.org/W3082895349","https://openalex.org/W4213079790","https://openalex.org/W2248239756","https://openalex.org/W3086377361"],"abstract_inverted_index":{"This":[0],"study":[1,181],"presents":[2],"an":[3],"enhanced":[4],"convolutional":[5],"neural":[6],"network":[7],"(CNN)":[8],"model":[9,71,220],"integrated":[10],"with":[11,172],"Explainable":[12],"Artificial":[13],"Intelligence":[14],"(XAI)":[15],"techniques":[16],"for":[17,189],"accurate":[18],"prediction":[19,87],"and":[20,63,77,89,114,140,149,186,193,210,222],"interpretation":[21],"of":[22,138,152,167,199],"wheat":[23,56,191],"crop":[24],"diseases.":[25],"The":[26,69,81,135,180],"aim":[27],"is":[28,155],"to":[29,42,92,97,121,132,174,218],"streamline":[30],"the":[31,39,49,123,127,165,205],"detection":[32],"process":[33],"while":[34],"offering":[35],"transparent":[36],"insights":[37],"into":[38],"model\u2019s":[40,124],"decision-making":[41],"support":[43],"effective":[44],"disease":[45,178],"management.":[46],"To":[47],"evaluate":[48],"model,":[50],"a":[51,143,183],"dataset":[52,206],"was":[53],"collected":[54],"from":[55],"fields":[57],"in":[58,86,100,158],"Kotli,":[59],"Azad":[60],"Kashmir,":[61],"Pakistan,":[62],"tested":[64],"across":[65,207],"multiple":[66],"data":[67,217],"splits.":[68],"proposed":[70],"demonstrates":[72],"improved":[73],"stability,":[74],"faster":[75],"convergence,":[76],"higher":[78],"classification":[79,133],"accuracy.":[80],"results":[82],"show":[83],"significant":[84],"improvements":[85],"accuracy":[88,99],"stability":[90],"compared":[91],"prior":[93],"works,":[94],"achieving":[95],"up":[96],"100%":[98],"certain":[101],"configurations.":[102],"In":[103],"addition,":[104],"XAI":[105,141,173],"methods":[106],"such":[107,214],"as":[108,215],"Local":[109],"Interpretable":[110],"Model-agnostic":[111],"Explanations":[112,117],"(LIME)":[113],"Shapley":[115],"Additive":[116],"(SHAP)":[118],"were":[119],"employed":[120],"explain":[122],"predictions,":[125],"highlighting":[126],"most":[128],"influential":[129],"features":[130],"contributing":[131],"decisions.":[134],"combined":[136],"use":[137],"CNN":[139],"offers":[142,182],"dual":[144],"benefit:":[145],"strong":[146],"predictive":[147],"performance":[148],"clear":[150],"interpretability":[151],"outcomes,":[153],"which":[154],"especially":[156],"critical":[157],"real-world":[159],"agricultural":[160,195],"applications.":[161],"These":[162],"findings":[163],"underscore":[164],"potential":[166],"integrating":[168],"deep":[169],"learning":[170],"models":[171],"advance":[175],"automated":[176],"plant":[177],"detection.":[179],"precise,":[184],"reliable,":[185],"interpretable":[187],"solution":[188],"improving":[190],"production":[192],"promoting":[194],"sustainability.":[196],"Future":[197],"extensions":[198],"this":[200],"work":[201],"may":[202],"include":[203],"scaling":[204],"broader":[208],"regions":[209],"incorporating":[211],"additional":[212],"modalities":[213],"environmental":[216],"enhance":[219],"robustness":[221],"generalization.":[223]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":3}],"updated_date":"2026-03-27T14:29:43.386196","created_date":"2025-10-10T00:00:00"}