{"id":"https://openalex.org/W4389314731","doi":"https://doi.org/10.1145/3627377.3627448","title":"End-to-End Remote Sensing Image Scene Classification with Vision Transformers","display_name":"End-to-End Remote Sensing Image Scene Classification with Vision Transformers","publication_year":2023,"publication_date":"2023-09-22","ids":{"openalex":"https://openalex.org/W4389314731","doi":"https://doi.org/10.1145/3627377.3627448"},"language":"en","primary_location":{"id":"doi:10.1145/3627377.3627448","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3627377.3627448","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2023 6th International Conference on Big Data Technologies","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5000427803","display_name":"Hao Yuan","orcid":"https://orcid.org/0009-0006-6280-5324"},"institutions":[{"id":"https://openalex.org/I34949971","display_name":"University of Jinan","ror":"https://ror.org/02mjz6f26","country_code":"CN","type":"education","lineage":["https://openalex.org/I34949971"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hao Yuan","raw_affiliation_strings":["School of Information Science and Engineering, University of Jinan, China, \rChina High-resolution Earth Observation System Shandong Center of Data and Application, University of Jinan, China and \rShandong Provincial Key Laboratory of Network Based Intelligent Computing, University of Jinan, China"],"raw_orcid":"https://orcid.org/0009-0006-6280-5324","affiliations":[{"raw_affiliation_string":"School of Information Science and Engineering, University of Jinan, China, \rChina High-resolution Earth Observation System Shandong Center of Data and Application, University of Jinan, China and \rShandong Provincial Key Laboratory of Network Based Intelligent Computing, University of Jinan, China","institution_ids":["https://openalex.org/I34949971"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101988429","display_name":"Kun Liu","orcid":"https://orcid.org/0009-0004-5735-2696"},"institutions":[{"id":"https://openalex.org/I34949971","display_name":"University of Jinan","ror":"https://ror.org/02mjz6f26","country_code":"CN","type":"education","lineage":["https://openalex.org/I34949971"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kun Liu","raw_affiliation_strings":["School of Information Science and Engineering, University of Jinan, China, \rChina High-resolution Earth Observation System Shandong Center of Data and Application, University of Jinan, China and \rShandong Provincial Key Laboratory of Network Based Intelligent Computing, University of Jinan, China"],"raw_orcid":"https://orcid.org/0009-0004-5735-2696","affiliations":[{"raw_affiliation_string":"School of Information Science and Engineering, University of Jinan, China, \rChina High-resolution Earth Observation System Shandong Center of Data and Application, University of Jinan, China and \rShandong Provincial Key Laboratory of Network Based Intelligent Computing, University of Jinan, China","institution_ids":["https://openalex.org/I34949971"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5027577036","display_name":"Jiechuan Shi","orcid":"https://orcid.org/0009-0005-4977-1097"},"institutions":[{"id":"https://openalex.org/I34949971","display_name":"University of Jinan","ror":"https://ror.org/02mjz6f26","country_code":"CN","type":"education","lineage":["https://openalex.org/I34949971"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiechuan Shi","raw_affiliation_strings":["School of Information Science and Engineering, University of Jinan, China, \rChina High-resolution Earth Observation System Shandong Center of Data and Application, University of Jinan, China and \rShandong Provincial Key Laboratory of Network Based Intelligent Computing, University of Jinan, China"],"raw_orcid":"https://orcid.org/0009-0005-4977-1097","affiliations":[{"raw_affiliation_string":"School of Information Science and Engineering, University of Jinan, China, \rChina High-resolution Earth Observation System Shandong Center of Data and Application, University of Jinan, China and \rShandong Provincial Key Laboratory of Network Based Intelligent Computing, University of Jinan, China","institution_ids":["https://openalex.org/I34949971"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5040845253","display_name":"Can Wang","orcid":"https://orcid.org/0009-0002-2058-478X"},"institutions":[{"id":"https://openalex.org/I34949971","display_name":"University of Jinan","ror":"https://ror.org/02mjz6f26","country_code":"CN","type":"education","lineage":["https://openalex.org/I34949971"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Can Wang","raw_affiliation_strings":["School of Information Science and Engineering, University of Jinan, China, \rChina High-resolution Earth Observation System Shandong Center of Data and Application, University of Jinan, China and \rShandong Provincial Key Laboratory of Network Based Intelligent Computing, University of Jinan, China"],"raw_orcid":"https://orcid.org/0009-0002-2058-478X","affiliations":[{"raw_affiliation_string":"School of Information Science and Engineering, University of Jinan, China, \rChina High-resolution Earth Observation System Shandong Center of Data and Application, University of Jinan, China and \rShandong Provincial Key Laboratory of Network Based Intelligent Computing, University of Jinan, China","institution_ids":["https://openalex.org/I34949971"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5001713541","display_name":"Weiwei Wang","orcid":"https://orcid.org/0009-0005-7851-206X"},"institutions":[{"id":"https://openalex.org/I152269853","display_name":"Qilu University of Technology","ror":"https://ror.org/04hyzq608","country_code":"CN","type":"education","lineage":["https://openalex.org/I152269853"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weiwei Wang","raw_affiliation_strings":["QiLu Research Institute, China"],"raw_orcid":"https://orcid.org/0009-0005-7851-206X","affiliations":[{"raw_affiliation_string":"QiLu Research Institute, China","institution_ids":["https://openalex.org/I152269853"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"365","last_page":"371"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9997000098228455,"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":0.9997000098228455,"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":0.9937000274658203,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9934999942779541,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7615343332290649},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6453753113746643},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6312289834022522},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.550306499004364},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.5460715889930725},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5265684127807617},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.5136184096336365},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4506042003631592},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.4047716557979584},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.21506306529045105},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.11105361580848694},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.08304235339164734},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.07458975911140442}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7615343332290649},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6453753113746643},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6312289834022522},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.550306499004364},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.5460715889930725},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5265684127807617},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.5136184096336365},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4506042003631592},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.4047716557979584},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.21506306529045105},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.11105361580848694},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.08304235339164734},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.07458975911140442},{"id":"https://openalex.org/C165801399","wikidata":"https://www.wikidata.org/wiki/Q25428","display_name":"Voltage","level":2,"score":0.0},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3627377.3627448","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3627377.3627448","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2023 6th International Conference on Big Data Technologies","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/17","score":0.4099999964237213,"display_name":"Partnerships for the goals"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W1676314349","https://openalex.org/W1981276685","https://openalex.org/W1989316905","https://openalex.org/W2097117768","https://openalex.org/W2098676252","https://openalex.org/W2291068538","https://openalex.org/W2515866431","https://openalex.org/W2618530766","https://openalex.org/W2727875856","https://openalex.org/W2890732922","https://openalex.org/W2988666519","https://openalex.org/W2992382424","https://openalex.org/W3037215700","https://openalex.org/W3040156639","https://openalex.org/W3047889186","https://openalex.org/W3105577662","https://openalex.org/W4200394859","https://openalex.org/W4295122555"],"related_works":["https://openalex.org/W4226493464","https://openalex.org/W4312417841","https://openalex.org/W3193565141","https://openalex.org/W3133861977","https://openalex.org/W3167935049","https://openalex.org/W3029198973","https://openalex.org/W2952813363","https://openalex.org/W4378678253","https://openalex.org/W2911497689","https://openalex.org/W4360783045"],"abstract_inverted_index":{"In":[0],"recent":[1],"years,":[2],"the":[3,33,47,58,81,108,129,155,184,206],"development":[4],"of":[5,35,60,67,80,199],"deep":[6,97],"learning":[7],"technology":[8],"has":[9,115,163],"led":[10],"to":[11,45,146,189],"widespread":[12],"attention":[13],"on":[14,54,89,102,136,176,205],"Vision":[15,55,82,93,137,193],"Transformer":[16,83,94,138,194],"(ViT)":[17],"as":[18],"an":[19,29],"emerging":[20],"image":[21,26,50,132,172,180],"classification":[22,27,51,78,133,197],"method.":[23],"Remote":[24],"sensing":[25,49,91,131,160,171,179],"is":[28,85,95],"important":[30],"task":[31],"in":[32,65,112,119,158],"field":[34],"remote":[36,48,90,130,159,170,178],"sensing,":[37],"with":[38,168],"extensive":[39],"application":[40],"prospects.":[41],"This":[42],"paper":[43],"aims":[44],"explore":[46],"method":[52,134],"based":[53,101,135],"Transformer,":[56],"addressing":[57],"limitations":[59],"traditional":[61,147],"convolutional":[62,148],"neural":[63,98,149],"networks":[64],"terms":[66],"global":[68,109,156],"perception":[69],"capability,":[70],"context":[71,110],"information":[72,111],"retrieval,":[73],"and":[74,87,114,142,162,203,210],"positional":[75],"encoding.":[76],"The":[77],"performance":[79,118],"model":[84,100,185],"evaluated":[86],"compared":[88,188],"datasets.":[92],"a":[96],"network":[99],"self-attention":[103],"mechanism":[104],"that":[105,128,183],"can":[106,152],"capture":[107,154],"images":[113,161],"achieved":[116],"remarkable":[117],"various":[120],"computer":[121],"vision":[122],"tasks.":[123],"Furthermore,":[124],"experimental":[125],"results":[126,175],"demonstrate":[127],"exhibits":[139],"outstanding":[140],"accuracy":[141],"generalization":[143],"ability.":[144],"Compared":[145],"networks,":[150],"it":[151],"better":[153,164],"features":[157],"scalability":[165],"when":[166],"dealing":[167],"large-scale":[169],"data.":[173],"Experimental":[174],"different":[177],"datasets":[181],"show":[182],"performs":[186],"well":[187],"state-of-the-art":[190],"methods.":[191],"Specifically,":[192],"achieves":[195],"average":[196],"accuracies":[198],"95.41%,":[200],"98.26%,":[201],"93.74%":[202],"95.25%":[204],"AID,":[207],"UC-Merced,":[208],"NWPU-RESISC45":[209],"Optimal31":[211],"datasets,":[212],"respectively.":[213]},"counts_by_year":[{"year":2025,"cited_by_count":2}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}