{"id":"https://openalex.org/W4414143162","doi":"https://doi.org/10.32604/cmc.2025.064359","title":"Enhanced Plant Species Identification through Metadata Fusion and Vision Transformer Integration","display_name":"Enhanced Plant Species Identification through Metadata Fusion and Vision Transformer Integration","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4414143162","doi":"https://doi.org/10.32604/cmc.2025.064359"},"language":"en","primary_location":{"id":"doi:10.32604/cmc.2025.064359","is_oa":true,"landing_page_url":"https://doi.org/10.32604/cmc.2025.064359","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.2025.064359","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5082022472","display_name":"Javed Hassan","orcid":"https://orcid.org/0000-0001-7696-3653"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Hassan Javed","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5084679881","display_name":"Labiba Gillani Fahad","orcid":"https://orcid.org/0000-0003-2892-9068"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Labiba Gillani Fahad","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108749093","display_name":"Syed Fahad Tahir","orcid":"https://orcid.org/0000-0001-8444-4300"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Syed Fahad Tahir","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5082020424","display_name":"Mehdi Hassan","orcid":"https://orcid.org/0000-0003-4629-2582"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Mehdi Hassan","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5090343976","display_name":"Hani Alquhayz","orcid":"https://orcid.org/0000-0001-8445-7742"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hani Alquhayz","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5082022472"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.18729131,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"85","issue":"2","first_page":"3981","last_page":"3996"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10616","display_name":"Smart Agriculture and AI","score":0.9912999868392944,"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":0.9912999868392944,"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/metadata","display_name":"Metadata","score":0.7501000165939331},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.5418000221252441},{"id":"https://openalex.org/keywords/sensor-fusion","display_name":"Sensor fusion","score":0.46889999508857727},{"id":"https://openalex.org/keywords/plant-species","display_name":"Plant species","score":0.3540000021457672},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.3012000024318695},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.29600000381469727},{"id":"https://openalex.org/keywords/image-stitching","display_name":"Image stitching","score":0.2921000123023987}],"concepts":[{"id":"https://openalex.org/C93518851","wikidata":"https://www.wikidata.org/wiki/Q180160","display_name":"Metadata","level":2,"score":0.7501000165939331},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7203999757766724},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.5418000221252441},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5170000195503235},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.47049999237060547},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.46889999508857727},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3700000047683716},{"id":"https://openalex.org/C2985179745","wikidata":"https://www.wikidata.org/wiki/Q131449","display_name":"Plant species","level":2,"score":0.3540000021457672},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.3012000024318695},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.29600000381469727},{"id":"https://openalex.org/C29081049","wikidata":"https://www.wikidata.org/wiki/Q1364242","display_name":"Image stitching","level":2,"score":0.2921000123023987},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.2919999957084656},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.2863999903202057},{"id":"https://openalex.org/C55282118","wikidata":"https://www.wikidata.org/wiki/Q252683","display_name":"Snapshot (computer storage)","level":2,"score":0.2831999957561493},{"id":"https://openalex.org/C187691185","wikidata":"https://www.wikidata.org/wiki/Q2020720","display_name":"Grid","level":2,"score":0.2759000062942505},{"id":"https://openalex.org/C72634772","wikidata":"https://www.wikidata.org/wiki/Q386824","display_name":"Data integration","level":2,"score":0.2669000029563904},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.2653000056743622},{"id":"https://openalex.org/C58642233","wikidata":"https://www.wikidata.org/wiki/Q8269924","display_name":"Taxonomy (biology)","level":2,"score":0.25769999623298645},{"id":"https://openalex.org/C173414695","wikidata":"https://www.wikidata.org/wiki/Q5510276","display_name":"Fusion mechanism","level":4,"score":0.2547000050544739}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.32604/cmc.2025.064359","is_oa":true,"landing_page_url":"https://doi.org/10.32604/cmc.2025.064359","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.2025.064359","is_oa":true,"landing_page_url":"https://doi.org/10.32604/cmc.2025.064359","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":13,"referenced_works":["https://openalex.org/W2100358124","https://openalex.org/W2148143831","https://openalex.org/W2161558103","https://openalex.org/W2170505850","https://openalex.org/W2473156356","https://openalex.org/W2613340652","https://openalex.org/W2769625730","https://openalex.org/W2795866616","https://openalex.org/W2997171867","https://openalex.org/W3188201332","https://openalex.org/W4297510489","https://openalex.org/W4394565294","https://openalex.org/W4405531700"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2058118494","https://openalex.org/W2392768766","https://openalex.org/W2382021449","https://openalex.org/W2095118173","https://openalex.org/W2106424170","https://openalex.org/W1985426483","https://openalex.org/W2501188010"],"abstract_inverted_index":{"Accurate":[0],"plant":[1],"species":[2,35],"classification":[3,21,102,165],"is":[4],"essential":[5],"for":[6,70,168,198],"many":[7],"applications,":[8],"such":[9,83],"as":[10,84],"biodiversity":[11],"conservation,":[12],"ecological":[13,98,203],"research,":[14],"and":[15,27,47,90,97,104,124,172,176,205],"sustainable":[16],"agricultural":[17,207],"practices.":[18],"Traditional":[19],"morphological":[20],"methods":[22],"are":[23],"inherently":[24],"slow,":[25],"labour-intensive,":[26],"prone":[28],"to":[29,48,185],"inaccuracies,":[30],"especially":[31,107],"when":[32],"distinguishing":[33],"between":[34],"exhibiting":[36],"visual":[37,72,96],"similarities":[38],"or":[39],"high":[40],"intra-species":[41],"variability.":[42],"To":[43],"address":[44],"these":[45],"limitations":[46],"overcome":[49],"the":[50,181],"constraints":[51],"of":[52,95,121,129,139,151],"image-only":[53],"approaches,":[54],"we":[55],"introduce":[56],"a":[57,75],"novel":[58],"Artificial":[59],"Intelligence-driven":[60],"framework.":[61],"This":[62,93,191],"approach":[63,162,193],"integrates":[64],"robust":[65],"Vision":[66],"Transformer":[67],"(ViT)":[68],"models":[69],"advanced":[71,206],"analysis":[73,155],"with":[74],"multi-modal":[76],"data":[77],"fusion":[78,161],"strategy,":[79],"incorporating":[80],"contextual":[81],"metadata":[82,160],"precise":[85,199],"environmental":[86],"conditions,":[87],"geographic":[88],"location,":[89],"phenological":[91],"traits.":[92],"combination":[94],"cues":[99],"significantly":[100],"enhances":[101],"accuracy":[103],"robustness,":[105],"proving":[106],"vital":[108],"in":[109],"complex,":[110],"heterogeneous":[111],"real-world":[112],"environments.":[113],"The":[114],"proposed":[115],"model":[116,182],"achieves":[117],"an":[118],"impressive":[119],"97.27%":[120],"test":[122],"accuracy,":[123],"Mean":[125],"Reciprocal":[126],"Rank":[127],"(MRR)":[128],"0.9842":[130],"that":[131,158],"demonstrates":[132],"strong":[133],"generalization":[134],"capabilities.":[135],"Furthermore,":[136],"efficient":[137],"utilization":[138],"high-performance":[140],"GPU":[141],"resources":[142],"(RTX":[143],"3090,":[144],"18":[145],"GB":[146],"memory)":[147],"ensures":[148],"scalable":[149],"processing":[150],"high-dimensional":[152],"data.":[153],"Comparative":[154],"consistently":[156],"confirms":[157],"our":[159],"substantially":[163],"improves":[164],"performance,":[166],"particularly":[167],"morphologically":[169],"similar":[170],"species,":[171,187],"through":[173],"principled":[174],"self-supervised":[175],"transfer":[177],"learning":[178],"from":[179],"ImageNet,":[180],"adapts":[183],"efficiently":[184],"new":[186],"ensuring":[188],"enhanced":[189],"generalization.":[190],"comprehensive":[192],"holds":[194],"profound":[195],"practical":[196],"implications":[197],"conservation":[200],"initiatives,":[201],"rigorous":[202],"monitoring,":[204],"management.":[208]},"counts_by_year":[],"updated_date":"2026-03-07T16:01:11.037858","created_date":"2025-10-10T00:00:00"}