{"id":"https://openalex.org/W4407691650","doi":"https://doi.org/10.1109/iceic64972.2025.10879691","title":"Local Overlapping Attentional Selection with VIT for Image Classification in Remote Sensing","display_name":"Local Overlapping Attentional Selection with VIT for Image Classification in Remote Sensing","publication_year":2025,"publication_date":"2025-01-19","ids":{"openalex":"https://openalex.org/W4407691650","doi":"https://doi.org/10.1109/iceic64972.2025.10879691"},"language":"en","primary_location":{"id":"doi:10.1109/iceic64972.2025.10879691","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iceic64972.2025.10879691","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 International Conference on Electronics, Information, and Communication (ICEIC)","raw_type":"proceedings-article"},"type":"article","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/A5095773291","display_name":"Changman Zou","orcid":"https://orcid.org/0009-0001-2056-8299"},"institutions":[{"id":"https://openalex.org/I71007489","display_name":"Kyungnam University","ror":"https://ror.org/037pkxm09","country_code":"KR","type":"education","lineage":["https://openalex.org/I71007489"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"ChangMan Zou","raw_affiliation_strings":["University of Kyungnam,Department of IT Convergence Engineering,Changwon,Republic of Korea,51767"],"affiliations":[{"raw_affiliation_string":"University of Kyungnam,Department of IT Convergence Engineering,Changwon,Republic of Korea,51767","institution_ids":["https://openalex.org/I71007489"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5035813083","display_name":"Wang\u2010Su Jeon","orcid":"https://orcid.org/0000-0001-8887-2513"},"institutions":[{"id":"https://openalex.org/I71007489","display_name":"Kyungnam University","ror":"https://ror.org/037pkxm09","country_code":"KR","type":"education","lineage":["https://openalex.org/I71007489"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Wang-Su Jeon","raw_affiliation_strings":["University of Kyungnam,Department of Computer Engineering,Changwon,Republic of Korea,51767"],"affiliations":[{"raw_affiliation_string":"University of Kyungnam,Department of Computer Engineering,Changwon,Republic of Korea,51767","institution_ids":["https://openalex.org/I71007489"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5018274633","display_name":"Sang\u2010Yong Rhee","orcid":null},"institutions":[{"id":"https://openalex.org/I71007489","display_name":"Kyungnam University","ror":"https://ror.org/037pkxm09","country_code":"KR","type":"education","lineage":["https://openalex.org/I71007489"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Sang-Yong Rhee","raw_affiliation_strings":["University of Kyungnam,Department of Computer Engineering,Changwon,Republic of Korea,51767"],"affiliations":[{"raw_affiliation_string":"University of Kyungnam,Department of Computer Engineering,Changwon,Republic of Korea,51767","institution_ids":["https://openalex.org/I71007489"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5095773291"],"corresponding_institution_ids":["https://openalex.org/I71007489"],"apc_list":null,"apc_paid":null,"fwci":1.1713,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.77324605,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.8819000124931335,"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":0.8819000124931335,"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/T10320","display_name":"Neural Networks and Applications","score":0.8352000117301941,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T10057","display_name":"Face and Expression Recognition","score":0.7699000239372253,"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/selection","display_name":"Selection (genetic algorithm)","score":0.7438605427742004},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7281185388565063},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5034934878349304},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4435670077800751},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3205067813396454}],"concepts":[{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.7438605427742004},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7281185388565063},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5034934878349304},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4435670077800751},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3205067813396454}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iceic64972.2025.10879691","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iceic64972.2025.10879691","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 International Conference on Electronics, Information, and Communication (ICEIC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G3395038292","display_name":null,"funder_award_id":"2021RIS-003","funder_id":"https://openalex.org/F4320311649","funder_display_name":"Ministry of Education"},{"id":"https://openalex.org/G5293985778","display_name":null,"funder_award_id":"SG20240201","funder_id":"https://openalex.org/F4320321681","funder_display_name":"Ministry of Trade, Industry and Energy"}],"funders":[{"id":"https://openalex.org/F4320311649","display_name":"Ministry of Education","ror":"https://ror.org/036nq5137"},{"id":"https://openalex.org/F4320321681","display_name":"Ministry of Trade, Industry and Energy","ror":"https://ror.org/008nkqk13"},{"id":"https://openalex.org/F4320322120","display_name":"National Research Foundation of Korea","ror":"https://ror.org/013aysd81"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W2515866431","https://openalex.org/W2744582969","https://openalex.org/W2974770574","https://openalex.org/W2986888765","https://openalex.org/W3004916592","https://openalex.org/W3045603631","https://openalex.org/W3047889186","https://openalex.org/W3111811104","https://openalex.org/W3113299742","https://openalex.org/W3128592650","https://openalex.org/W3138516171","https://openalex.org/W3151130473","https://openalex.org/W3168972675","https://openalex.org/W3207506706","https://openalex.org/W4294982860","https://openalex.org/W4315778358","https://openalex.org/W4388936936","https://openalex.org/W4390826350","https://openalex.org/W4398145143","https://openalex.org/W4398767247","https://openalex.org/W4400229049"],"related_works":["https://openalex.org/W2772917594","https://openalex.org/W2036807459","https://openalex.org/W2058170566","https://openalex.org/W2755342338","https://openalex.org/W2166024367","https://openalex.org/W3116076068","https://openalex.org/W2229312674","https://openalex.org/W2951359407","https://openalex.org/W2079911747","https://openalex.org/W1969923398"],"abstract_inverted_index":{"Remote":[0],"sensing":[1,67,156],"image":[2,101,157],"classification":[3,73,158],"presents":[4],"unique":[5],"challenges":[6],"due":[7],"to":[8,122,139],"the":[9,12,15,22,46,60,72,86,97,130,136],"complexity":[10],"of":[11],"scenes":[13,141],"and":[14,34,79,93,111,113,125,145],"variability":[16],"in":[17],"visual":[18],"features":[19],"caused":[20],"by":[21,75],"overhead":[23],"perspective.":[24],"Traditional":[25],"convolutional":[26],"neural":[27],"networks":[28],"(CNNs)":[29],"struggle":[30],"with":[31,142],"long-range":[32],"dependencies":[33],"extracting":[35],"sufficient":[36],"context":[37],"for":[38,65,89,153],"accurate":[39],"classification.":[40,69],"To":[41],"address":[42],"this,":[43],"we":[44],"propose":[45],"LSViT":[47,70,105],"model,":[48],"a":[49,54],"novel":[50],"approach":[51],"that":[52],"incorporates":[53],"local":[55,94,131],"attention":[56,132],"selection":[57,133],"module":[58,134],"into":[59],"Transformer":[61],"architecture,":[62],"specifically":[63],"designed":[64],"remote":[66,155],"scene":[68],"enhances":[71,135],"performance":[74],"selecting":[76],"discriminative":[77],"tokens":[78],"removing":[80],"redundant":[81],"information.":[82],"Our":[83],"model":[84],"leverages":[85],"Transformer's":[87],"capacity":[88],"capturing":[90],"both":[91],"global":[92],"features,":[95],"improving":[96],"focus":[98],"on":[99,106],"important":[100],"regions.":[102],"We":[103],"evaluate":[104],"two":[107],"benchmark":[108],"datasets,":[109],"AID":[110],"NWPU-RESISC45,":[112],"demonstrate":[114],"its":[115],"competitive":[116],"performance,":[117],"achieving":[118],"state-of-the-art":[119],"accuracy":[120],"compared":[121],"traditional":[123],"CNN":[124],"other":[126],"Transformer-based":[127],"methods.":[128],"Notably,":[129],"model's":[137],"ability":[138],"classify":[140],"overlapping":[143],"objects":[144],"complex":[146],"backgrounds,":[147],"making":[148],"it":[149],"an":[150],"effective":[151],"solution":[152],"large-scale":[154],"tasks.":[159]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-03-25T14:56:36.534964","created_date":"2025-10-10T00:00:00"}