{"id":"https://openalex.org/W3164432294","doi":"https://doi.org/10.1109/lgrs.2021.3071624","title":"Semantic Segmentation of Remote Sensing Image Based on Regional Self-Attention Mechanism","display_name":"Semantic Segmentation of Remote Sensing Image Based on Regional Self-Attention Mechanism","publication_year":2021,"publication_date":"2021-05-26","ids":{"openalex":"https://openalex.org/W3164432294","doi":"https://doi.org/10.1109/lgrs.2021.3071624","mag":"3164432294"},"language":"en","primary_location":{"id":"doi:10.1109/lgrs.2021.3071624","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lgrs.2021.3071624","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/A5036886150","display_name":"Danpei Zhao","orcid":"https://orcid.org/0000-0001-6701-0471"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Danpei Zhao","raw_affiliation_strings":["Image Processing Center, School of Astronautics, Beihang University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0001-6701-0471","affiliations":[{"raw_affiliation_string":"Image Processing Center, School of Astronautics, Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100455038","display_name":"Chenxu Wang","orcid":"https://orcid.org/0000-0002-1174-8933"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chenxu Wang","raw_affiliation_strings":["Image Processing Center, School of Astronautics, Beihang University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-1174-8933","affiliations":[{"raw_affiliation_string":"Image Processing Center, School of Astronautics, Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101410329","display_name":"Yue Gao","orcid":"https://orcid.org/0000-0002-5020-586X"},"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":"Yue Gao","raw_affiliation_strings":["Space Star Technology Company Ltd., Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Space Star Technology Company Ltd., Beijing, China","institution_ids":["https://openalex.org/I194716290"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5058849690","display_name":"Zhenwei Shi","orcid":"https://orcid.org/0000-0002-4772-3172"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhenwei Shi","raw_affiliation_strings":["Image Processing Center, School of Astronautics, Beihang University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-4772-3172","affiliations":[{"raw_affiliation_string":"Image Processing Center, School of Astronautics, Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5052196775","display_name":"Fengying Xie","orcid":"https://orcid.org/0000-0002-5681-2345"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fengying Xie","raw_affiliation_strings":["Image Processing Center, School of Astronautics, Beihang University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-5681-2345","affiliations":[{"raw_affiliation_string":"Image Processing Center, School of Astronautics, Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5036886150"],"corresponding_institution_ids":["https://openalex.org/I82880672"],"apc_list":null,"apc_paid":null,"fwci":2.6214,"has_fulltext":false,"cited_by_count":35,"citation_normalized_percentile":{"value":0.9149445,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":"19","issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9995999932289124,"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"}},"topics":[{"id":"https://openalex.org/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9995999932289124,"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/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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9986000061035156,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7542116641998291},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.7079669237136841},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.6678413152694702},{"id":"https://openalex.org/keywords/intersection","display_name":"Intersection (aeronautics)","score":0.5750854015350342},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.5738155245780945},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5212860107421875},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.518657386302948},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.49971914291381836},{"id":"https://openalex.org/keywords/semantics","display_name":"Semantics (computer science)","score":0.47508755326271057},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.42483603954315186},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.41603440046310425},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.41121408343315125},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3667011260986328},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.1396770477294922},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.13341665267944336},{"id":"https://openalex.org/keywords/cartography","display_name":"Cartography","score":0.09709376096725464}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7542116641998291},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.7079669237136841},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.6678413152694702},{"id":"https://openalex.org/C64543145","wikidata":"https://www.wikidata.org/wiki/Q162942","display_name":"Intersection (aeronautics)","level":2,"score":0.5750854015350342},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.5738155245780945},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5212860107421875},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.518657386302948},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.49971914291381836},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.47508755326271057},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.42483603954315186},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.41603440046310425},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.41121408343315125},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3667011260986328},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.1396770477294922},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.13341665267944336},{"id":"https://openalex.org/C58640448","wikidata":"https://www.wikidata.org/wiki/Q42515","display_name":"Cartography","level":1,"score":0.09709376096725464},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/lgrs.2021.3071624","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lgrs.2021.3071624","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":[],"awards":[{"id":"https://openalex.org/G444973788","display_name":null,"funder_award_id":"2019YFC1510905","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"}],"funders":[{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":16,"referenced_works":["https://openalex.org/W1903029394","https://openalex.org/W2194775991","https://openalex.org/W2412782625","https://openalex.org/W2560023338","https://openalex.org/W2563705555","https://openalex.org/W2787091153","https://openalex.org/W2799213142","https://openalex.org/W2895340641","https://openalex.org/W2955058313","https://openalex.org/W2963091558","https://openalex.org/W2963727650","https://openalex.org/W2981689412","https://openalex.org/W3109301572","https://openalex.org/W6766844300","https://openalex.org/W6772565011","https://openalex.org/W6775483769"],"related_works":["https://openalex.org/W2348909947","https://openalex.org/W4285411112","https://openalex.org/W4292672442","https://openalex.org/W2085033728","https://openalex.org/W2362101859","https://openalex.org/W2171299904","https://openalex.org/W2791431590","https://openalex.org/W1978900583","https://openalex.org/W2350688482","https://openalex.org/W2053575972"],"abstract_inverted_index":{"In":[0],"remote":[1],"sensing":[2],"images":[3,92],"(RSIs),":[4],"accurate":[5],"semantic":[6,30,121,136],"segmentation":[7,31,122,137],"faces":[8],"more":[9,88],"challenges":[10],"because":[11],"of":[12,25,37,43,63,107,113,161],"small":[13],"targets,":[14],"unbalanced":[15],"categories,":[16],"and":[17,110,133,165],"complex":[18],"scenes.":[19],"Restricted":[20],"by":[21,60],"local":[22],"receptive":[23],"field":[24],"convolution":[26],"layers,":[27],"the":[28,41,61,67,71,78,83,97,105,111,129,134,155],"traditional":[29,98],"models":[32,127],"cannot":[33],"use":[34],"global":[35],"information":[36,68],"RSIs.":[38],"According":[39],"to":[40],"characteristics":[42],"RSIs,":[44],"we":[45],"propose":[46],"an":[47],"RSANet":[48,101,145],"based":[49],"on":[50,128],"regional":[51],"self-attention":[52,99],"mechanism.":[53],"Our":[54,116],"model":[55,117],"is":[56,87],"no":[57],"longer":[58],"limited":[59],"locality":[62],"convolution,":[64],"but":[65],"transfers":[66],"flow":[69],"in":[70,82,159],"whole":[72],"image.":[73],"It":[74],"can":[75,102,118],"mine":[76],"out":[77],"relationship":[79],"between":[80],"pixels":[81],"surrounding":[84],"areas,":[85],"which":[86],"logical":[89],"for":[90],"understanding":[91],"content.":[93],"Moreover,":[94],"compared":[95],"with":[96],"mechanism,":[100],"effectively":[103],"reduce":[104],"noise":[106],"feature":[108],"maps":[109],"interference":[112],"redundant":[114],"features.":[115],"get":[119],"better":[120],"results":[123],"than":[124,154],"other":[125],"current":[126],"DroneDeploy":[130],"data":[131,138],"set":[132],"Chreos":[135],"set.":[139],"The":[140],"experiments":[141],"show":[142],"that":[143],"our":[144],"achieves":[146],"2%":[147],"higher":[148],"mean":[149],"intersection":[150],"over":[151],"union":[152],"(mIoU)":[153],"baseline":[156],"model,":[157],"especially":[158],"terms":[160],"fineness,":[162],"edge":[163],"integrity,":[164],"classification":[166],"accuracy.":[167]},"counts_by_year":[{"year":2025,"cited_by_count":8},{"year":2024,"cited_by_count":11},{"year":2023,"cited_by_count":13},{"year":2022,"cited_by_count":3}],"updated_date":"2025-12-23T23:11:35.936235","created_date":"2025-10-10T00:00:00"}