{"id":"https://openalex.org/W4410401273","doi":"https://doi.org/10.3390/jimaging11050156","title":"Unleashing the Potential of Residual and Dual-Stream Transformers for the Remote Sensing Image Analysis","display_name":"Unleashing the Potential of Residual and Dual-Stream Transformers for the Remote Sensing Image Analysis","publication_year":2025,"publication_date":"2025-05-15","ids":{"openalex":"https://openalex.org/W4410401273","doi":"https://doi.org/10.3390/jimaging11050156","pmid":"https://pubmed.ncbi.nlm.nih.gov/40423013"},"language":"en","primary_location":{"id":"doi:10.3390/jimaging11050156","is_oa":true,"landing_page_url":"https://doi.org/10.3390/jimaging11050156","pdf_url":"https://www.mdpi.com/2313-433X/11/5/156/pdf?version=1747379210","source":{"id":"https://openalex.org/S2736465063","display_name":"Journal of Imaging","issn_l":"2313-433X","issn":["2313-433X"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Imaging","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/2313-433X/11/5/156/pdf?version=1747379210","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101626270","display_name":"Priya Mittal","orcid":"https://orcid.org/0000-0003-2171-0717"},"institutions":[{"id":"https://openalex.org/I74319210","display_name":"Chitkara University","ror":"https://ror.org/057d6z539","country_code":"IN","type":"education","lineage":["https://openalex.org/I74319210"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Priya Mittal","raw_affiliation_strings":["Chitkara University Institute of Engineering and Technology, Chitkara University, Rajpura 140401, Punjab, India"],"raw_orcid":"https://orcid.org/0000-0003-2171-0717","affiliations":[{"raw_affiliation_string":"Chitkara University Institute of Engineering and Technology, Chitkara University, Rajpura 140401, Punjab, India","institution_ids":["https://openalex.org/I74319210"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076238519","display_name":"Vishesh Tanwar","orcid":"https://orcid.org/0000-0001-7215-0794"},"institutions":[{"id":"https://openalex.org/I74319210","display_name":"Chitkara University","ror":"https://ror.org/057d6z539","country_code":"IN","type":"education","lineage":["https://openalex.org/I74319210"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Vishesh Tanwar","raw_affiliation_strings":["Chitkara University Institute of Engineering and Technology, Chitkara University, Rajpura 140401, Punjab, India"],"raw_orcid":"https://orcid.org/0000-0001-7215-0794","affiliations":[{"raw_affiliation_string":"Chitkara University Institute of Engineering and Technology, Chitkara University, Rajpura 140401, Punjab, India","institution_ids":["https://openalex.org/I74319210"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5057555412","display_name":"Bhisham Sharma","orcid":null},"institutions":[{"id":"https://openalex.org/I74319210","display_name":"Chitkara University","ror":"https://ror.org/057d6z539","country_code":"IN","type":"education","lineage":["https://openalex.org/I74319210"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Bhisham Sharma","raw_affiliation_strings":["Centre of Research Impact and Outcome, Chitkara University, Rajpura 140401, Punjab, India"],"raw_orcid":"https://orcid.org/0000-0002-3400-3504","affiliations":[{"raw_affiliation_string":"Centre of Research Impact and Outcome, Chitkara University, Rajpura 140401, Punjab, India","institution_ids":["https://openalex.org/I74319210"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5078412004","display_name":"Dhirendra Prasad Yadav","orcid":"https://orcid.org/0000-0001-9349-3964"},"institutions":[{"id":"https://openalex.org/I82571370","display_name":"GLA University","ror":"https://ror.org/05fnxgv12","country_code":"IN","type":"education","lineage":["https://openalex.org/I82571370"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Dhirendra Prasad Yadav","raw_affiliation_strings":["Department of Computer Engineering & Applications, G.L.A. University, Mathura 281406, Uttar Pradesh, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Engineering & Applications, G.L.A. University, Mathura 281406, Uttar Pradesh, India","institution_ids":["https://openalex.org/I82571370"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5057555412","https://openalex.org/A5078412004"],"corresponding_institution_ids":["https://openalex.org/I74319210","https://openalex.org/I82571370"],"apc_list":{"value":1600,"currency":"CHF","value_usd":1732},"apc_paid":{"value":1600,"currency":"CHF","value_usd":1732},"fwci":1.846,"has_fulltext":true,"cited_by_count":2,"citation_normalized_percentile":{"value":0.86144299,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":98},"biblio":{"volume":"11","issue":"5","first_page":"156","last_page":"156"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9998999834060669,"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":0.9998999834060669,"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/T13890","display_name":"Remote Sensing and Land Use","score":0.9922000169754028,"subfield":{"id":"https://openalex.org/subfields/1902","display_name":"Atmospheric Science"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10111","display_name":"Remote Sensing in Agriculture","score":0.9921000003814697,"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/computer-science","display_name":"Computer science","score":0.8164732456207275},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6324690580368042},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6030258536338806},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.5915179252624512},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5727913975715637},{"id":"https://openalex.org/keywords/residual","display_name":"Residual","score":0.5534871220588684},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5191258788108826},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.45177406072616577},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.45036646723747253},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.4375118017196655},{"id":"https://openalex.org/keywords/categorization","display_name":"Categorization","score":0.4364888072013855},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.35487091541290283},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3260113596916199},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.0856785774230957}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8164732456207275},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6324690580368042},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6030258536338806},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.5915179252624512},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5727913975715637},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.5534871220588684},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5191258788108826},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.45177406072616577},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.45036646723747253},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.4375118017196655},{"id":"https://openalex.org/C94124525","wikidata":"https://www.wikidata.org/wiki/Q912550","display_name":"Categorization","level":2,"score":0.4364888072013855},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.35487091541290283},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3260113596916199},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.0856785774230957},{"id":"https://openalex.org/C165801399","wikidata":"https://www.wikidata.org/wiki/Q25428","display_name":"Voltage","level":2,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.3390/jimaging11050156","is_oa":true,"landing_page_url":"https://doi.org/10.3390/jimaging11050156","pdf_url":"https://www.mdpi.com/2313-433X/11/5/156/pdf?version=1747379210","source":{"id":"https://openalex.org/S2736465063","display_name":"Journal of Imaging","issn_l":"2313-433X","issn":["2313-433X"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Imaging","raw_type":"journal-article"},{"id":"pmid:40423013","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/40423013","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of imaging","raw_type":null},{"id":"pmh:oai:doaj.org/article:b38e49c9f7e04ed988af4eb8b27f465c","is_oa":true,"landing_page_url":"https://doaj.org/article/b38e49c9f7e04ed988af4eb8b27f465c","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","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":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Journal of Imaging, Vol 11, Iss 5, p 156 (2025)","raw_type":"article"},{"id":"pmh:oai:pubmedcentral.nih.gov:12112853","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/12112853","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"J Imaging","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/jimaging11050156","is_oa":true,"landing_page_url":"https://doi.org/10.3390/jimaging11050156","pdf_url":"https://www.mdpi.com/2313-433X/11/5/156/pdf?version=1747379210","source":{"id":"https://openalex.org/S2736465063","display_name":"Journal of Imaging","issn_l":"2313-433X","issn":["2313-433X"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Imaging","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","score":0.6299999952316284,"id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4410401273.pdf","grobid_xml":"https://content.openalex.org/works/W4410401273.grobid-xml"},"referenced_works_count":45,"referenced_works":["https://openalex.org/W1968591910","https://openalex.org/W2001123951","https://openalex.org/W2002281921","https://openalex.org/W2105032938","https://openalex.org/W2533228971","https://openalex.org/W2570214200","https://openalex.org/W2599408268","https://openalex.org/W2733443012","https://openalex.org/W2808436940","https://openalex.org/W2963333059","https://openalex.org/W2991488782","https://openalex.org/W2991647354","https://openalex.org/W3012326541","https://openalex.org/W3128655704","https://openalex.org/W4293370522","https://openalex.org/W4295101840","https://openalex.org/W4311156295","https://openalex.org/W4312828762","https://openalex.org/W4313485077","https://openalex.org/W4314947406","https://openalex.org/W4319866415","https://openalex.org/W4321615196","https://openalex.org/W4323064994","https://openalex.org/W4352977361","https://openalex.org/W4362653113","https://openalex.org/W4366547391","https://openalex.org/W4378192102","https://openalex.org/W4385338433","https://openalex.org/W4386065496","https://openalex.org/W4388266836","https://openalex.org/W4388692010","https://openalex.org/W4388938319","https://openalex.org/W4390604208","https://openalex.org/W4391365617","https://openalex.org/W4392148427","https://openalex.org/W4394713316","https://openalex.org/W4395097743","https://openalex.org/W4396877743","https://openalex.org/W4400351485","https://openalex.org/W4400771408","https://openalex.org/W4400912955","https://openalex.org/W4401879137","https://openalex.org/W4403127247","https://openalex.org/W4403331566","https://openalex.org/W6855567645"],"related_works":["https://openalex.org/W2165912799","https://openalex.org/W2735662278","https://openalex.org/W2382615723","https://openalex.org/W4405331580","https://openalex.org/W4311804456","https://openalex.org/W1987484445","https://openalex.org/W2623658258","https://openalex.org/W2143413548","https://openalex.org/W1969219540","https://openalex.org/W2370459448"],"abstract_inverted_index":{"The":[0,63,86,188,222],"categorization":[1],"of":[2,55,195,202],"remote":[3,244],"sensing":[4,245],"satellite":[5,219],"imagery":[6],"is":[7,89,129,142],"crucial":[8],"for":[9,91,204,211,243],"various":[10],"applications,":[11],"including":[12],"environmental":[13],"monitoring,":[14],"urban":[15],"planning,":[16],"and":[17,24,40,58,75,95,107,126,140,165,182,199,208,234],"disaster":[18],"management.":[19],"Convolutional":[20],"Neural":[21],"Networks":[22],"(CNNs)":[23],"Vision":[25,59],"Transformers":[26],"(ViTs)":[27],"have":[28],"exhibited":[29],"exceptional":[30],"performance":[31],"among":[32],"deep":[33],"learning":[34],"techniques,":[35],"excelling":[36],"in":[37,114,218],"feature":[38,93,167],"extraction":[39,94],"representational":[41],"learning.":[42],"This":[43],"paper":[44],"presents":[45],"a":[46,240],"hybrid":[47,116,228],"dual-stream":[48,64,227],"ResV2ViT":[49,176,229],"model":[50,68,161,177,190,230],"that":[51,225],"combines":[52],"the":[53,67,100,115,118,132,145,152,160,174,179,205,212,226],"advantages":[54],"ResNet50":[56],"V2":[57],"Transformer":[60,146],"(ViT)":[61],"architectures.":[62],"approach":[65],"allows":[66,159],"to":[69,135,144,147,151,162],"extract":[70],"both":[71],"local":[72,137],"spatial":[73,138,153],"features":[74],"global":[76,108,149],"contextual":[77,109],"information":[78],"by":[79],"processing":[80],"data":[81],"through":[82],"two":[83,123,157],"complementary":[84],"pathways.":[85],"ResNet50V2":[87],"component":[88],"utilized":[90],"hierarchical":[92],"captures":[96],"short-range":[97],"dependencies,":[98],"whereas":[99],"ViT":[101],"module":[102],"efficiently":[103],"models":[104],"long-range":[105],"dependencies":[106],"information.":[110],"After":[111],"position":[112],"embedding":[113],"model,":[117],"tokens":[119],"are":[120],"bifurcated":[121],"into":[122,131],"parts:":[124],"q1":[125,128],"q2.":[127],"passed":[130],"convolutional":[133],"block":[134],"refine":[136],"details,":[139],"q2":[141],"given":[143],"provide":[148],"attention":[150],"feature.":[154],"Combining":[155],"these":[156],"architectures":[158],"acquire":[163],"low-level":[164],"high-level":[166],"representations,":[168],"improving":[169],"classification":[170],"performance.":[171],"We":[172],"assess":[173],"proposed":[175,189],"using":[178],"RSI-CB256":[180],"dataset":[181,184,207],"another":[183],"with":[185,197],"21":[186],"classes.":[187],"attains":[191],"an":[192],"average":[193],"accuracy":[194,210],"99.91%,":[196],"precision":[198],"F1":[200],"score":[201],"99.90%":[203],"first":[206],"98.75%":[209],"second":[213],"dataset,":[214],"illustrating":[215],"its":[216],"efficacy":[217],"image":[220],"classification.":[221],"findings":[223],"demonstrate":[224],"surpasses":[231],"traditional":[232],"CNN":[233],"Transformer-based":[235],"models,":[236],"establishing":[237],"it":[238],"as":[239],"formidable":[241],"framework":[242],"applications.":[246]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}
