{"id":"https://openalex.org/W7134241444","doi":"https://doi.org/10.48550/arxiv.2603.05844","title":"Remote Sensing Image Classification Using Deep Ensemble Learning","display_name":"Remote Sensing Image Classification Using Deep Ensemble Learning","publication_year":2026,"publication_date":"2026-03-06","ids":{"openalex":"https://openalex.org/W7134241444","doi":"https://doi.org/10.48550/arxiv.2603.05844"},"language":null,"primary_location":{"id":"pmh:doi:10.48550/arxiv.2603.05844","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"publisher-specific-oa","license_id":"https://openalex.org/licenses/publisher-specific-oa","version":"submittedVersion","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":null,"any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5031805530","display_name":"Niful Islam","orcid":"https://orcid.org/0009-0003-3725-7213"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Islam, Niful","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128629425","display_name":"Md. Rayhan Ahmed","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ahmed, Md. Rayhan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5022918060","display_name":"Nur Mohammad Fahad","orcid":"https://orcid.org/0009-0000-5445-6925"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Fahad, Nur Mohammad","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5054256777","display_name":"Salekul Islam","orcid":"https://orcid.org/0000-0002-7262-0060"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Islam, Salekul","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128399026","display_name":"A. K. M. Muzahidul Islam","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Islam, A. K. M. Muzahidul","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5087616870","display_name":"Md. Saddam Hossain Mukta","orcid":"https://orcid.org/0000-0003-2675-5471"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Mukta, Saddam","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5067504579","display_name":"Swakkhar Shatabda","orcid":"https://orcid.org/0000-0003-0669-072X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shatabda, Swakkhar","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"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/T10689","display_name":"Remote-Sensing Image Classification","score":0.7712000012397766,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.7712000012397766,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.05090000107884407,"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/T11659","display_name":"Advanced Image Fusion Techniques","score":0.04859999939799309,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"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":0.684499979019165},{"id":"https://openalex.org/keywords/bottleneck","display_name":"Bottleneck","score":0.6184999942779541},{"id":"https://openalex.org/keywords/usable","display_name":"USable","score":0.5503000020980835},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.5235000252723694},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.46239998936653137},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.44940000772476196},{"id":"https://openalex.org/keywords/ensemble-learning","display_name":"Ensemble learning","score":0.4189000129699707},{"id":"https://openalex.org/keywords/boosting","display_name":"Boosting (machine learning)","score":0.41370001435279846},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.40290001034736633}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.792900025844574},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.684499979019165},{"id":"https://openalex.org/C2780513914","wikidata":"https://www.wikidata.org/wiki/Q18210350","display_name":"Bottleneck","level":2,"score":0.6184999942779541},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6122999787330627},{"id":"https://openalex.org/C2780615836","wikidata":"https://www.wikidata.org/wiki/Q2471869","display_name":"USable","level":2,"score":0.5503000020980835},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.5235000252723694},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.46239998936653137},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.44940000772476196},{"id":"https://openalex.org/C45942800","wikidata":"https://www.wikidata.org/wiki/Q245652","display_name":"Ensemble learning","level":2,"score":0.4189000129699707},{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.41370001435279846},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.40290001034736633},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.39079999923706055},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.39070001244544983},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.38929998874664307},{"id":"https://openalex.org/C183365957","wikidata":"https://www.wikidata.org/wiki/Q17140402","display_name":"Remote sensing application","level":3,"score":0.36340001225471497},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.35260000824928284},{"id":"https://openalex.org/C69744172","wikidata":"https://www.wikidata.org/wiki/Q860822","display_name":"Image fusion","level":3,"score":0.34549999237060547},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.3359000086784363},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.30559998750686646},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.305400013923645},{"id":"https://openalex.org/C132964779","wikidata":"https://www.wikidata.org/wiki/Q2110223","display_name":"Raw data","level":2,"score":0.2985000014305115},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.29100000858306885},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.2775000035762787},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.27379998564720154},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.2572999894618988},{"id":"https://openalex.org/C10929652","wikidata":"https://www.wikidata.org/wiki/Q7279985","display_name":"Radar imaging","level":3,"score":0.257099986076355},{"id":"https://openalex.org/C110083411","wikidata":"https://www.wikidata.org/wiki/Q1744628","display_name":"Statistical classification","level":2,"score":0.2565000057220459},{"id":"https://openalex.org/C119898033","wikidata":"https://www.wikidata.org/wiki/Q3433888","display_name":"Ensemble forecasting","level":2,"score":0.2554999887943268}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:doi:10.48550/arxiv.2603.05844","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"publisher-specific-oa","license_id":"https://openalex.org/licenses/publisher-specific-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},{"id":"doi:10.48550/arxiv.2603.05844","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.05844","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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"pmh:doi:10.48550/arxiv.2603.05844","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"publisher-specific-oa","license_id":"https://openalex.org/licenses/publisher-specific-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},"sustainable_development_goals":[{"score":0.4244079291820526,"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Remote":[0],"sensing":[1,123],"imagery":[2,23],"plays":[3],"a":[4,98,110],"crucial":[5],"role":[6],"in":[7],"many":[8],"applications":[9],"and":[10,26,69,85,95,119,142,145,167,175,184],"requires":[11],"accurate":[12],"computerized":[13],"classification":[14,17],"techniques.":[15],"Reliable":[16],"is":[18],"essential":[19],"for":[20,37,121],"transforming":[21],"raw":[22],"into":[24],"structured":[25],"usable":[27],"information.":[28,52],"While":[29],"Convolutional":[30],"Neural":[31],"Networks":[32],"(CNNs)":[33],"are":[34],"mostly":[35],"used":[36],"image":[38,124],"classification,":[39],"they":[40],"excel":[41],"at":[42,149],"local":[43],"feature":[44,103],"extraction,":[45],"but":[46],"struggle":[47],"to":[48,73,91,194],"capture":[49],"global":[50],"contextual":[51],"Vision":[53],"Transformers":[54],"(ViTs)":[55],"address":[56],"this":[57,106],"limitation":[58],"through":[59,154],"self":[60],"attention":[61],"mechanisms":[62],"that":[63,113,139],"model":[64,112],"long-range":[65],"dependencies.":[66],"Integrating":[67],"CNNs":[68,118],"ViTs,":[70],"therefore,":[71],"leads":[72],"better":[74],"performance":[75,93,129],"than":[76],"standalone":[77],"architectures.":[78],"However,":[79],"the":[80,115,128,131,150,171,186,189],"use":[81,197],"of":[82,117,162,188,198],"additional":[83],"CNN":[84,141],"ViT":[86,143],"components":[87],"does":[88],"not":[89],"lead":[90],"further":[92],"improvement":[94],"instead":[96],"introduces":[97],"bottleneck":[99],"caused":[100],"by":[101],"redundant":[102],"representations.":[104],"In":[105],"research,":[107],"we":[108],"propose":[109],"fusion":[111,137],"combines":[114],"strengths":[116],"ViTs":[120],"remote":[122],"classification.":[125],"To":[126],"overcome":[127],"bottleneck,":[130],"proposed":[132,157,190],"approach":[133],"trains":[134],"four":[135],"independent":[136],"models":[138],"integrate":[140],"backbones":[144],"combine":[146],"their":[147],"outputs":[148],"final":[151],"prediction":[152],"stage":[153],"ensembling.":[155],"The":[156],"method":[158],"achieves":[159],"accuracy":[160],"rates":[161],"98.10":[163],"percent,":[164,166],"94.46":[165],"95.45":[168],"percent":[169],"on":[170],"UC":[172],"Merced,":[173],"RSSCN7,":[174],"MSRSI":[176],"datasets,":[177],"respectively.":[178],"These":[179],"results":[180],"outperform":[181],"competing":[182],"architectures":[183],"highlight":[185],"effectiveness":[187],"solution,":[191],"particularly":[192],"due":[193],"its":[195],"efficient":[196],"computational":[199],"resources":[200],"during":[201],"training.":[202]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-03-10T00:00:00"}
