{"id":"https://openalex.org/W4313591257","doi":"https://doi.org/10.1109/lgrs.2023.3233979","title":"Dual-Range Context Aggregation for Efficient Semantic Segmentation in Remote Sensing Images","display_name":"Dual-Range Context Aggregation for Efficient Semantic Segmentation in Remote Sensing Images","publication_year":2023,"publication_date":"2023-01-01","ids":{"openalex":"https://openalex.org/W4313591257","doi":"https://doi.org/10.1109/lgrs.2023.3233979"},"language":"en","primary_location":{"id":"doi:10.1109/lgrs.2023.3233979","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lgrs.2023.3233979","pdf_url":null,"source":{"id":"https://openalex.org/S126920919","display_name":"IEEE Geoscience and Remote Sensing Letters","issn_l":"1545-598X","issn":["1545-598X","1558-0571"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Geoscience and Remote Sensing Letters","raw_type":"journal-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/A5022902828","display_name":"Guangjun He","orcid":"https://orcid.org/0000-0002-2614-8850"},"institutions":[{"id":"https://openalex.org/I194716290","display_name":"China Academy of Space Technology","ror":"https://ror.org/025397a59","country_code":"CN","type":"government","lineage":["https://openalex.org/I194716290","https://openalex.org/I2802615301"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guangjun He","raw_affiliation_strings":["State Key Laboratory of Space-Ground Integrated Information Technology, Space Star Technology Company Ltd., Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-2614-8850","affiliations":[{"raw_affiliation_string":"State Key Laboratory of Space-Ground Integrated Information Technology, Space Star Technology Company Ltd., Beijing, China","institution_ids":["https://openalex.org/I194716290"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5077090072","display_name":"Zhe Dong","orcid":"https://orcid.org/0000-0002-9734-4904"},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhe Dong","raw_affiliation_strings":["School of Electronics and Information Engineering, Harbin Institute of Technology, Harbin, China"],"raw_orcid":"https://orcid.org/0000-0002-9734-4904","affiliations":[{"raw_affiliation_string":"School of Electronics and Information Engineering, Harbin Institute of Technology, Harbin, China","institution_ids":["https://openalex.org/I204983213"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5041045446","display_name":"Pengming Feng","orcid":"https://orcid.org/0000-0001-5853-8100"},"institutions":[{"id":"https://openalex.org/I194716290","display_name":"China Academy of Space Technology","ror":"https://ror.org/025397a59","country_code":"CN","type":"government","lineage":["https://openalex.org/I194716290","https://openalex.org/I2802615301"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Pengming Feng","raw_affiliation_strings":["State Key Laboratory of Space-Ground Integrated Information Technology, Space Star Technology Company Ltd., Beijing, China"],"raw_orcid":"https://orcid.org/0000-0001-5853-8100","affiliations":[{"raw_affiliation_string":"State Key Laboratory of Space-Ground Integrated Information Technology, Space Star Technology Company Ltd., Beijing, China","institution_ids":["https://openalex.org/I194716290"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5033678891","display_name":"Dilxat Muhtar","orcid":null},"institutions":[{"id":"https://openalex.org/I881766915","display_name":"Nanjing University","ror":"https://ror.org/01rxvg760","country_code":"CN","type":"education","lineage":["https://openalex.org/I881766915"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dilxat Muhtar","raw_affiliation_strings":["School of Geography and Ocean Science, Nanjing University, Nanjing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Geography and Ocean Science, Nanjing University, Nanjing, China","institution_ids":["https://openalex.org/I881766915"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100693229","display_name":"Xueliang Zhang","orcid":"https://orcid.org/0000-0001-6188-0257"},"institutions":[{"id":"https://openalex.org/I881766915","display_name":"Nanjing University","ror":"https://ror.org/01rxvg760","country_code":"CN","type":"education","lineage":["https://openalex.org/I881766915"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xueliang Zhang","raw_affiliation_strings":["School of Geography and Ocean Science, Nanjing University, Nanjing, China"],"raw_orcid":"https://orcid.org/0000-0001-6188-0257","affiliations":[{"raw_affiliation_string":"School of Geography and Ocean Science, Nanjing University, Nanjing, China","institution_ids":["https://openalex.org/I881766915"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.2939,"has_fulltext":false,"cited_by_count":12,"citation_normalized_percentile":{"value":0.79835037,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":"20","issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9991999864578247,"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":0.9991999864578247,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9988999962806702,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9976999759674072,"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":0.8224889039993286},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.6710786819458008},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6223824620246887},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5540810227394104},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.5176442265510559},{"id":"https://openalex.org/keywords/intersection","display_name":"Intersection (aeronautics)","score":0.45179155468940735},{"id":"https://openalex.org/keywords/range","display_name":"Range (aeronautics)","score":0.42363429069519043},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.39741256833076477},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3663526177406311}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8224889039993286},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.6710786819458008},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6223824620246887},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5540810227394104},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.5176442265510559},{"id":"https://openalex.org/C64543145","wikidata":"https://www.wikidata.org/wiki/Q162942","display_name":"Intersection (aeronautics)","level":2,"score":0.45179155468940735},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.42363429069519043},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.39741256833076477},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3663526177406311},{"id":"https://openalex.org/C146978453","wikidata":"https://www.wikidata.org/wiki/Q3798668","display_name":"Aerospace engineering","level":1,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/lgrs.2023.3233979","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lgrs.2023.3233979","pdf_url":null,"source":{"id":"https://openalex.org/S126920919","display_name":"IEEE Geoscience and Remote Sensing Letters","issn_l":"1545-598X","issn":["1545-598X","1558-0571"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Geoscience and Remote Sensing Letters","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.49000000953674316,"id":"https://metadata.un.org/sdg/17","display_name":"Partnerships for the goals"}],"awards":[{"id":"https://openalex.org/G3793418368","display_name":null,"funder_award_id":"61806018","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6392665283","display_name":null,"funder_award_id":"41801291","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8203269020","display_name":"\u5f31\u6807\u8bb0\u6761\u4ef6\u4e0b\u9ad8\u5206\u8fa8\u7387\u9065\u611f\u56fe\u50cf\u8bed\u4e49\u5206\u5272\u5173\u952e\u6280\u672f\u7814\u7a76","funder_award_id":"42071297","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":38,"referenced_works":["https://openalex.org/W1903029394","https://openalex.org/W2560023338","https://openalex.org/W2630837129","https://openalex.org/W2787091153","https://openalex.org/W2798122215","https://openalex.org/W2886934227","https://openalex.org/W2955058313","https://openalex.org/W2955813853","https://openalex.org/W2962782553","https://openalex.org/W2963378109","https://openalex.org/W2963890956","https://openalex.org/W2964217532","https://openalex.org/W2967731069","https://openalex.org/W2991488782","https://openalex.org/W2995766874","https://openalex.org/W2996106355","https://openalex.org/W2997225633","https://openalex.org/W3019771380","https://openalex.org/W3105367394","https://openalex.org/W3109998321","https://openalex.org/W3138516171","https://openalex.org/W3157967435","https://openalex.org/W3161825146","https://openalex.org/W3165745140","https://openalex.org/W3183174367","https://openalex.org/W3190334976","https://openalex.org/W3194371117","https://openalex.org/W3207809295","https://openalex.org/W4212969531","https://openalex.org/W4283450732","https://openalex.org/W4293406525","https://openalex.org/W4302275239","https://openalex.org/W4362470605","https://openalex.org/W6717372056","https://openalex.org/W6739696289","https://openalex.org/W6750469568","https://openalex.org/W6751733626","https://openalex.org/W6795300077"],"related_works":["https://openalex.org/W2348909947","https://openalex.org/W4292672442","https://openalex.org/W2362101859","https://openalex.org/W2791431590","https://openalex.org/W2941610985","https://openalex.org/W4235810826","https://openalex.org/W3000105423","https://openalex.org/W2350688482","https://openalex.org/W2122135111","https://openalex.org/W1522196789"],"abstract_inverted_index":{"Although":[0],"introducing":[1],"self-attention":[2,82],"mechanisms":[3],"is":[4,63,83,103,121],"beneficial":[5],"to":[6,65,92,105,123],"establish":[7],"long-range":[8],"dependencies":[9],"and":[10,29,70,78,100,127,138,144,161,180],"explore":[11],"global":[12,72],"context":[13,45,59,74],"information":[14,107],"in":[15,26,111],"the":[16,67,71,94,133,145,176,184],"task":[17],"of":[18],"remote":[19,51],"sensing":[20,52],"image":[21,53],"semantic":[22,54,73],"segmentation,":[23],"it":[24],"results":[25],"expensive":[27],"computation":[28],"large":[30],"memory":[31],"cost.":[32],"In":[33,164],"this":[34,38],"letter,":[35],"we":[36],"address":[37],"dilemma":[39],"by":[40,76,86],"proposing":[41],"a":[42,57,98,113,125],"lightweight":[43,101],"dual-range":[44,58],"aggregation":[46,60],"network":[47],"(LDCANet)":[48],"for":[49,136],"efficient":[50,117,128],"segmentation.":[55],"First,":[56],"module":[61],"(DCAM)":[62],"designed":[64],"aggregate":[66],"local":[68],"features":[69],"acquired":[75],"convolutions":[77],"self-attention,":[79],"respectively,":[80],"where":[81],"implemented":[84],"easily":[85],"applying":[87],"two":[88],"cascaded":[89],"linear":[90,118],"layers":[91],"reduce":[93],"computational":[95,162],"complexity.":[96],"Furthermore,":[97],"simple":[99],"decoder":[102],"employed":[104],"combine":[106],"from":[108],"different":[109],"levels,":[110],"which":[112],"multilayer":[114],"perceptron":[115],"(MLP)-based":[116],"block":[119],"(ELB)":[120],"proposed":[122],"yield":[124],"strong":[126],"representation.":[129],"Experiments":[130],"conducted":[131],"on":[132,175,183],"International":[134],"Society":[135],"Photogrammetry":[137],"Remote":[139],"Sensing":[140],"(ISPRS)":[141],"Vaihingen":[142,178],"dataset":[143,148,179],"Gaofen":[146],"Image":[147],"(GID)":[149],"prove":[150],"that":[151],"our":[152,166],"LDCANet":[153],"achieves":[154,168],"an":[155],"excellent":[156],"trade-off":[157],"between":[158],"segmentation":[159],"accuracy":[160],"efficiency.":[163],"particular,":[165],"method":[167],"74.12%":[169],"mean":[170],"intersection":[171],"over":[172],"union":[173],"(mIoU)":[174],"ISPRS":[177],"61.42%":[181],"mIoU":[182],"GID":[185],"with":[186],"only":[187],"4.98-M":[188],"parameter":[189],"size.":[190]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":7},{"year":2023,"cited_by_count":1}],"updated_date":"2026-07-25T15:57:00.446498","created_date":"2025-10-10T00:00:00"}