{"id":"https://openalex.org/W4323897048","doi":"https://doi.org/10.1109/tgrs.2023.3256064","title":"Enhancing Multiscale Representations With Transformer for Remote Sensing Image Semantic Segmentation","display_name":"Enhancing Multiscale Representations With Transformer for Remote Sensing Image Semantic Segmentation","publication_year":2023,"publication_date":"2023-01-01","ids":{"openalex":"https://openalex.org/W4323897048","doi":"https://doi.org/10.1109/tgrs.2023.3256064"},"language":"en","primary_location":{"id":"doi:10.1109/tgrs.2023.3256064","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2023.3256064","pdf_url":null,"source":{"id":"https://openalex.org/S111326731","display_name":"IEEE Transactions on Geoscience and Remote Sensing","issn_l":"0196-2892","issn":["0196-2892","1558-0644"],"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 Transactions on Geoscience and Remote Sensing","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/A5100600700","display_name":"Tao Xiao","orcid":"https://orcid.org/0000-0002-3102-2582"},"institutions":[{"id":"https://openalex.org/I154099455","display_name":"Shandong University","ror":"https://ror.org/0207yh398","country_code":"CN","type":"education","lineage":["https://openalex.org/I154099455"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Tao Xiao","raw_affiliation_strings":["School of Software, Shandong University, Jinan, China"],"affiliations":[{"raw_affiliation_string":"School of Software, Shandong University, Jinan, China","institution_ids":["https://openalex.org/I154099455"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5048223720","display_name":"Yikun Liu","orcid":"https://orcid.org/0000-0001-5698-7623"},"institutions":[{"id":"https://openalex.org/I154099455","display_name":"Shandong University","ror":"https://ror.org/0207yh398","country_code":"CN","type":"education","lineage":["https://openalex.org/I154099455"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yikun Liu","raw_affiliation_strings":["School of Software, Shandong University, Jinan, China"],"affiliations":[{"raw_affiliation_string":"School of Software, Shandong University, Jinan, China","institution_ids":["https://openalex.org/I154099455"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103257748","display_name":"Yuwen Huang","orcid":"https://orcid.org/0000-0003-0452-4947"},"institutions":[{"id":"https://openalex.org/I4210136682","display_name":"Heze University","ror":"https://ror.org/041zje040","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210136682"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuwen Huang","raw_affiliation_strings":["School of Computer, Heze University, Heze, China"],"affiliations":[{"raw_affiliation_string":"School of Computer, Heze University, Heze, China","institution_ids":["https://openalex.org/I4210136682"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101638944","display_name":"Mingsong Li","orcid":"https://orcid.org/0000-0001-6133-3923"},"institutions":[{"id":"https://openalex.org/I154099455","display_name":"Shandong University","ror":"https://ror.org/0207yh398","country_code":"CN","type":"education","lineage":["https://openalex.org/I154099455"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Mingsong Li","raw_affiliation_strings":["School of Software, Shandong University, Jinan, China"],"affiliations":[{"raw_affiliation_string":"School of Software, Shandong University, Jinan, China","institution_ids":["https://openalex.org/I154099455"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5036183903","display_name":"Gongping Yang","orcid":"https://orcid.org/0000-0001-7637-2749"},"institutions":[{"id":"https://openalex.org/I4210136682","display_name":"Heze University","ror":"https://ror.org/041zje040","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210136682"]},{"id":"https://openalex.org/I154099455","display_name":"Shandong University","ror":"https://ror.org/0207yh398","country_code":"CN","type":"education","lineage":["https://openalex.org/I154099455"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Gongping Yang","raw_affiliation_strings":["School of Software, Shandong University, Jinan, China","School of Computer, Heze University, Heze, China"],"affiliations":[{"raw_affiliation_string":"School of Software, Shandong University, Jinan, China","institution_ids":["https://openalex.org/I154099455"]},{"raw_affiliation_string":"School of Computer, Heze University, Heze, China","institution_ids":["https://openalex.org/I4210136682"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5100600700"],"corresponding_institution_ids":["https://openalex.org/I154099455"],"apc_list":null,"apc_paid":null,"fwci":16.4503,"has_fulltext":false,"cited_by_count":102,"citation_normalized_percentile":{"value":0.99359222,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":"61","issue":null,"first_page":"1","last_page":"16"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9995999932289124,"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":0.9995999932289124,"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":0.9983000159263611,"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":0.989799976348877,"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":0.8555350303649902},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.6529536247253418},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6359513401985168},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5910998582839966},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5778455138206482},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.5189735293388367},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4547833502292633},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4542957842350006},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.44334810972213745},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.44160693883895874},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.35756272077560425}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8555350303649902},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.6529536247253418},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6359513401985168},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5910998582839966},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5778455138206482},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.5189735293388367},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4547833502292633},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4542957842350006},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.44334810972213745},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.44160693883895874},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.35756272077560425},{"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/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C165801399","wikidata":"https://www.wikidata.org/wiki/Q25428","display_name":"Voltage","level":2,"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":1,"locations":[{"id":"doi:10.1109/tgrs.2023.3256064","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2023.3256064","pdf_url":null,"source":{"id":"https://openalex.org/S111326731","display_name":"IEEE Transactions on Geoscience and Remote Sensing","issn_l":"0196-2892","issn":["0196-2892","1558-0644"],"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 Transactions on Geoscience and Remote Sensing","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G263609085","display_name":null,"funder_award_id":"U1903127","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6654980252","display_name":null,"funder_award_id":"tscy20200303","funder_id":"https://openalex.org/F4320329359","funder_display_name":"Taishan Industry Leading Talents"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320329359","display_name":"Taishan Industry Leading Talents","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":79,"referenced_works":["https://openalex.org/W1901129140","https://openalex.org/W1903029394","https://openalex.org/W2064094295","https://openalex.org/W2108598243","https://openalex.org/W2194775991","https://openalex.org/W2549139847","https://openalex.org/W2560023338","https://openalex.org/W2587540369","https://openalex.org/W2598666589","https://openalex.org/W2601564443","https://openalex.org/W2778539913","https://openalex.org/W2782861076","https://openalex.org/W2787091153","https://openalex.org/W2789643644","https://openalex.org/W2955058313","https://openalex.org/W2963091558","https://openalex.org/W2965383240","https://openalex.org/W2982220924","https://openalex.org/W3011147769","https://openalex.org/W3014641072","https://openalex.org/W3016719260","https://openalex.org/W3034427230","https://openalex.org/W3035022492","https://openalex.org/W3092462694","https://openalex.org/W3094502228","https://openalex.org/W3096609285","https://openalex.org/W3103092912","https://openalex.org/W3109788339","https://openalex.org/W3109998321","https://openalex.org/W3113343294","https://openalex.org/W3124149278","https://openalex.org/W3126080715","https://openalex.org/W3127338020","https://openalex.org/W3128055887","https://openalex.org/W3131500599","https://openalex.org/W3137572916","https://openalex.org/W3138136606","https://openalex.org/W3138516171","https://openalex.org/W3139633126","https://openalex.org/W3157525179","https://openalex.org/W3159663321","https://openalex.org/W3170841864","https://openalex.org/W3171125843","https://openalex.org/W3172661913","https://openalex.org/W3175515048","https://openalex.org/W3180045188","https://openalex.org/W3180355996","https://openalex.org/W3183174367","https://openalex.org/W3184761517","https://openalex.org/W3194371117","https://openalex.org/W3199444512","https://openalex.org/W3201623325","https://openalex.org/W3202370946","https://openalex.org/W3204166336","https://openalex.org/W3210958972","https://openalex.org/W3213557922","https://openalex.org/W3214821343","https://openalex.org/W4200142823","https://openalex.org/W4205138939","https://openalex.org/W4205365435","https://openalex.org/W4205379033","https://openalex.org/W4206377169","https://openalex.org/W4210727193","https://openalex.org/W4213253308","https://openalex.org/W4214493665","https://openalex.org/W4221153029","https://openalex.org/W4224269597","https://openalex.org/W4225123210","https://openalex.org/W4312977443","https://openalex.org/W4313007769","https://openalex.org/W4385245566","https://openalex.org/W6784094891","https://openalex.org/W6789386828","https://openalex.org/W6789705400","https://openalex.org/W6795308139","https://openalex.org/W6797175998","https://openalex.org/W6797399245","https://openalex.org/W6799579066","https://openalex.org/W6810073510"],"related_works":["https://openalex.org/W4390516098","https://openalex.org/W2181948922","https://openalex.org/W2384362569","https://openalex.org/W2142795561","https://openalex.org/W4205302943","https://openalex.org/W2561132942","https://openalex.org/W3155418658","https://openalex.org/W4243199227","https://openalex.org/W2379948177","https://openalex.org/W4309346246"],"abstract_inverted_index":{"Semantic":[0],"segmentation":[1],"is":[2,150,186,235],"an":[3,138,178],"extremely":[4],"challenging":[5],"task":[6],"in":[7,22,62,87,127,177],"high-resolution":[8,89],"remote":[9,214],"sensing":[10,215],"(HRRS)":[11],"images":[12],"as":[13,40,193],"objects":[14],"have":[15,28,36,60],"complex":[16],"spatial":[17,85,184],"layouts":[18],"and":[19,35,80,84,114,136,161,172,175,195,222],"enormous":[20],"variations":[21],"appearance.":[23],"Convolutional":[24],"neural":[25],"networks":[26],"(CNNs)":[27],"excellent":[29],"ability":[30],"to":[31,50,107,116,130,142,152,188],"extract":[32,153,189],"local":[33,78,159],"features":[34,79,160,199],"been":[37],"widely":[38],"applied":[39],"the":[41,51,75,109,123,128,133,148,157,170,207,218,225],"feature":[42,90,154],"extractor":[43],"for":[44,101],"various":[45],"vision":[46],"tasks.":[47],"However,":[48],"due":[49],"inherent":[52],"inductive":[53],"bias":[54],"of":[55,77,111,220,228],"convolution":[56,112],"operation,":[57],"CNNs":[58],"inevitably":[59],"limitations":[61],"modeling":[63],"long-range":[64],"dependencies.":[65],"Transformer":[66,115,129],"can":[67],"capture":[68],"global":[69,162,196],"representations":[70,163],"well,":[71],"but":[72],"unfortunately":[73],"ignores":[74],"details":[76],"has":[81],"high":[82],"computational":[83],"complexity":[86],"processing":[88],"maps.":[91],"In":[92,156],"this":[93],"paper,":[94],"we":[95],"propose":[96],"a":[97,182],"novel":[98],"hybrid":[99],"architecture":[100,140],"HRRS":[102],"image":[103],"segmentation,":[104],"termed":[105],"EMRT,":[106],"exploit":[108],"advantages":[110],"operations":[113],"enhance":[117],"multi-scale":[118,190],"representation":[119],"learning.":[120],"We":[121],"incorporate":[122],"deformable":[124],"self-attention":[125],"mechanism":[126],"automatically":[131],"adjust":[132],"receptive":[134],"field,":[135],"design":[137],"encoder-decoder":[139],"accordingly":[141],"achieve":[143],"efficient":[144],"context":[145],"modeling.":[146],"Specifically,":[147],"CNN":[149,171],"constructed":[151],"representations.":[155],"encoder,":[158],"at":[164,200,237],"different":[165,201],"resolutions":[166],"are":[167,203],"extracted":[168],"by":[169,206],"Transformer,":[173],"respectively,":[174],"fused":[176],"interactive":[179],"manner.":[180],"Moreover,":[181],"separate":[183],"branch":[185],"designed":[187],"contextual":[191],"information":[192],"queries,":[194],"dependencies":[197],"between":[198],"scales":[202],"efficiently":[204],"established":[205],"decoder.":[208],"Extensive":[209],"experiments":[210],"on":[211],"three":[212],"public":[213],"datasets":[216],"demonstrate":[217],"superiority":[219],"EMRT":[221],"indicate":[223],"that":[224],"overall":[226],"performance":[227],"our":[229],"method":[230],"outperforms":[231],"state-of-the-art":[232],"methods.":[233],"Code":[234],"available":[236],"https://github.com/peach-xiao/EMRT.":[238]},"counts_by_year":[{"year":2026,"cited_by_count":4},{"year":2025,"cited_by_count":45},{"year":2024,"cited_by_count":44},{"year":2023,"cited_by_count":9}],"updated_date":"2026-03-14T08:43:22.919905","created_date":"2025-10-10T00:00:00"}