{"id":"https://openalex.org/W7147415827","doi":"https://doi.org/10.48550/arxiv.2603.26761","title":"Tiny-ViT: A Compact Vision Transformer for Efficient and Explainable Potato Leaf Disease Classification","display_name":"Tiny-ViT: A Compact Vision Transformer for Efficient and Explainable Potato Leaf Disease Classification","publication_year":2026,"publication_date":"2026-03-23","ids":{"openalex":"https://openalex.org/W7147415827","doi":"https://doi.org/10.48550/arxiv.2603.26761"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2603.26761","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.26761","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2603.26761","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5125156541","display_name":"Shakil Mia","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Mia, Shakil","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5132572777","display_name":"Umme Habiba","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Habiba, Umme","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5092359950","display_name":"Urmi Akter","orcid":"https://orcid.org/0000-0002-5107-7492"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Akter, Urmi","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129404966","display_name":"SK Rezwana Quadir Raisa","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Raisa, SK Rezwana Quadir","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5117274331","display_name":"Jeba Maliha","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Maliha, Jeba","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5132689090","display_name":"Md. Iqbal Hossain","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hossain, Md. Iqbal","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5093932634","display_name":"Md. Shakhauat Hossan Sumon","orcid":"https://orcid.org/0000-0002-4240-9117"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sumon, Md. Shakhauat Hossan","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5125156541"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10616","display_name":"Smart Agriculture and AI","score":0.9807999730110168,"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":0.9807999730110168,"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/T12660","display_name":"Plant Disease Management Techniques","score":0.00279999990016222,"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/T10111","display_name":"Remote Sensing in Agriculture","score":0.0019000000320374966,"subfield":{"id":"https://openalex.org/subfields/2303","display_name":"Ecology"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/interpretability","display_name":"Interpretability","score":0.6459000110626221},{"id":"https://openalex.org/keywords/preprocessor","display_name":"Preprocessor","score":0.5080000162124634},{"id":"https://openalex.org/keywords/blight","display_name":"Blight","score":0.4691999852657318},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4674000144004822},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.4666999876499176},{"id":"https://openalex.org/keywords/plant-disease","display_name":"Plant disease","score":0.37209999561309814},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.34619998931884766}],"concepts":[{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.6459000110626221},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5511000156402588},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.5080000162124634},{"id":"https://openalex.org/C182076605","wikidata":"https://www.wikidata.org/wiki/Q4273292","display_name":"Blight","level":2,"score":0.4691999852657318},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4674000144004822},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.4666999876499176},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4302000105381012},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4047999978065491},{"id":"https://openalex.org/C3019235130","wikidata":"https://www.wikidata.org/wiki/Q188956","display_name":"Plant disease","level":2,"score":0.37209999561309814},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.34619998931884766},{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.3273000121116638},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.32679998874664307},{"id":"https://openalex.org/C5339829","wikidata":"https://www.wikidata.org/wiki/Q1425977","display_name":"Machine vision","level":2,"score":0.3237000107765198},{"id":"https://openalex.org/C2776091240","wikidata":"https://www.wikidata.org/wiki/Q106238460","display_name":"Plant identification","level":2,"score":0.31360000371932983},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.30239999294281006},{"id":"https://openalex.org/C2780092901","wikidata":"https://www.wikidata.org/wiki/Q3433612","display_name":"Correlation coefficient","level":2,"score":0.27799999713897705},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2678000032901764},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.2563999891281128},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.25220000743865967}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2603.26761","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.26761","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2603.26761","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.26761","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Early":[0,31,114],"and":[1,20,33,46,69,91,118,121,128,147,166,183,195,199,205,249],"precise":[2],"identification":[3],"of":[4,17,52,80,110,135,145,152,181,188,221,229,246,254],"plant":[5,255],"diseases,":[6,28],"especially":[7],"in":[8,43,100,216],"potato":[9,81],"crops":[10,19],"is":[11,66,88,105,155,203,224,239],"important":[12],"to":[13,39,62,97,131,171,251],"ensure":[14,21],"the":[15,18,22,122,133,136,173,206,222,227,236,252],"health":[16],"maximum":[23],"yield":[24,44],".":[25],"Potato":[26],"leaf":[27,82],"such":[29,160],"as":[30,161],"Blight":[32],"Late":[34,116],"Blight,":[35,115,117],"pose":[36],"significant":[37],"challenges":[38],"farmers,":[40],"often":[41],"resulting":[42],"losses":[45],"increased":[47],"pesticide":[48],"use.":[49],"Traditional":[50],"methods":[51,71],"detection":[53],"are":[54,59,72],"not":[55],"only":[56],"time-consuming,":[57],"but":[58],"also":[60],"subject":[61],"human":[63],"error,":[64],"which":[65,87,154,191,231],"why":[67],"automated":[68],"efficient":[70],"required.":[73],"The":[74,103,197],"paper":[75],"introduces":[76],"a":[77,89,108,148,176,240,243],"new":[78],"method":[79],"disease":[83,256],"classification":[84],"Tiny-ViT":[85,138,238],"model,":[86],"small":[90],"effective":[92],"Vision":[93],"Transformer":[94],"(ViT)":[95],"developed":[96],"be":[98],"used":[99],"resource-limited":[101],"systems.":[102],"model":[104,139,174,207,223],"tested":[106],"on":[107],"dataset":[109],"three":[111],"classes,":[112],"namely":[113],"Healthy":[119],"leaves,":[120],"preprocessing":[123],"procedures":[124],"include":[125],"resizing,":[126],"CLAHE,":[127],"Gaussian":[129],"blur":[130],"improve":[132],"quality":[134],"image.":[137],"has":[140,175],"an":[141],"impressive":[142],"test":[143],"accuracy":[144,151],"99.85%":[146],"mean":[149],"CV":[150],"99.82%":[153],"better":[156],"than":[157],"baseline":[158],"models":[159],"DEIT":[162],"Small,":[163],"SWIN":[164],"Tiny,":[165],"MobileViT":[167],"XS.":[168],"In":[169],"addition":[170],"this,":[172],"Matthews":[177],"Correlation":[178],"Coefficient":[179],"(MCC)":[180],"0.9990":[182],"narrow":[184],"confidence":[185],"intervals":[186],"(CI)":[187],"[0.9980,":[189],"0.9995],":[190],"indicates":[192],"high":[193,244],"reliability":[194],"generalization.":[196],"training":[198],"testing":[200],"inference":[201],"time":[202],"competitive,":[204],"exhibits":[208],"low":[209],"computational":[210],"expenses,":[211],"thereby,":[212],"making":[213],"it":[214],"applicable":[215],"real-time":[217],"applications.":[218],"Moreover,":[219],"interpretability":[220],"improved":[225],"with":[226,242],"help":[228],"GRAD-CAM,":[230],"identifies":[232],"diseased":[233],"areas.":[234],"Altogether,":[235],"proposed":[237],"solution":[241],"level":[245],"robustness,":[247],"efficiency,":[248],"explainability":[250],"problem":[253],"classification.":[257]},"counts_by_year":[],"updated_date":"2026-04-02T13:53:19.096889","created_date":"2026-04-02T00:00:00"}