{"id":"https://openalex.org/W2925148117","doi":"https://doi.org/10.1109/lgrs.2019.2901592","title":"Semantic Segmentation of Remote Sensing Images Using Multiscale Decoding Network","display_name":"Semantic Segmentation of Remote Sensing Images Using Multiscale Decoding Network","publication_year":2019,"publication_date":"2019-03-20","ids":{"openalex":"https://openalex.org/W2925148117","doi":"https://doi.org/10.1109/lgrs.2019.2901592","mag":"2925148117"},"language":"en","primary_location":{"id":"doi:10.1109/lgrs.2019.2901592","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lgrs.2019.2901592","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/A5100699785","display_name":"Xiaoqin Zhang","orcid":"https://orcid.org/0000-0003-0958-7285"},"institutions":[{"id":"https://openalex.org/I146620803","display_name":"Wenzhou University","ror":"https://ror.org/020hxh324","country_code":"CN","type":"education","lineage":["https://openalex.org/I146620803"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaoqin Zhang","raw_affiliation_strings":["Department of Computer Science, Wenzhou University, Wenzhou, China"],"raw_orcid":"https://orcid.org/0000-0003-0958-7285","affiliations":[{"raw_affiliation_string":"Department of Computer Science, Wenzhou University, Wenzhou, China","institution_ids":["https://openalex.org/I146620803"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5070635832","display_name":"Zhiheng Xiao","orcid":"https://orcid.org/0009-0003-8188-9074"},"institutions":[{"id":"https://openalex.org/I146620803","display_name":"Wenzhou University","ror":"https://ror.org/020hxh324","country_code":"CN","type":"education","lineage":["https://openalex.org/I146620803"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhiheng Xiao","raw_affiliation_strings":["Department of Computer Science, Wenzhou University, Wenzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Wenzhou University, Wenzhou, China","institution_ids":["https://openalex.org/I146620803"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100459319","display_name":"Dongyang Li","orcid":"https://orcid.org/0000-0002-0009-0064"},"institutions":[{"id":"https://openalex.org/I146620803","display_name":"Wenzhou University","ror":"https://ror.org/020hxh324","country_code":"CN","type":"education","lineage":["https://openalex.org/I146620803"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dongyang Li","raw_affiliation_strings":["Department of Computer Science, Wenzhou University, Wenzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Wenzhou University, Wenzhou, China","institution_ids":["https://openalex.org/I146620803"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5007888592","display_name":"Mingyu Fan","orcid":"https://orcid.org/0000-0002-0492-4708"},"institutions":[{"id":"https://openalex.org/I146620803","display_name":"Wenzhou University","ror":"https://ror.org/020hxh324","country_code":"CN","type":"education","lineage":["https://openalex.org/I146620803"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Mingyu Fan","raw_affiliation_strings":["Department of Computer Science, Wenzhou University, Wenzhou, China"],"raw_orcid":"https://orcid.org/0000-0002-0492-4708","affiliations":[{"raw_affiliation_string":"Department of Computer Science, Wenzhou University, Wenzhou, China","institution_ids":["https://openalex.org/I146620803"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100730692","display_name":"Li Zhao","orcid":"https://orcid.org/0000-0001-5787-2705"},"institutions":[{"id":"https://openalex.org/I146620803","display_name":"Wenzhou University","ror":"https://ror.org/020hxh324","country_code":"CN","type":"education","lineage":["https://openalex.org/I146620803"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Li Zhao","raw_affiliation_strings":["Department of Computer Science, Wenzhou University, Wenzhou, China"],"raw_orcid":"https://orcid.org/0000-0001-5787-2705","affiliations":[{"raw_affiliation_string":"Department of Computer Science, Wenzhou University, Wenzhou, China","institution_ids":["https://openalex.org/I146620803"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I146620803"],"apc_list":null,"apc_paid":null,"fwci":3.1848,"has_fulltext":false,"cited_by_count":34,"citation_normalized_percentile":{"value":0.92396945,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"16","issue":"9","first_page":"1492","last_page":"1496"},"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9991999864578247,"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/T11659","display_name":"Advanced Image Fusion Techniques","score":0.9976000189781189,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8461151123046875},{"id":"https://openalex.org/keywords/decoding-methods","display_name":"Decoding methods","score":0.8120933175086975},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.727196455001831},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.7140397429466248},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6656064987182617},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.6223911643028259},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6118807792663574},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6009783148765564},{"id":"https://openalex.org/keywords/path","display_name":"Path (computing)","score":0.5768946409225464},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.4617294371128082},{"id":"https://openalex.org/keywords/network-architecture","display_name":"Network architecture","score":0.43826907873153687},{"id":"https://openalex.org/keywords/convolutional-code","display_name":"Convolutional code","score":0.4301309883594513},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3508378863334656},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.27278274297714233},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.1999131739139557},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.06826618313789368}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8461151123046875},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.8120933175086975},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.727196455001831},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.7140397429466248},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6656064987182617},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.6223911643028259},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6118807792663574},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6009783148765564},{"id":"https://openalex.org/C2777735758","wikidata":"https://www.wikidata.org/wiki/Q817765","display_name":"Path (computing)","level":2,"score":0.5768946409225464},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.4617294371128082},{"id":"https://openalex.org/C193415008","wikidata":"https://www.wikidata.org/wiki/Q639681","display_name":"Network architecture","level":2,"score":0.43826907873153687},{"id":"https://openalex.org/C157899210","wikidata":"https://www.wikidata.org/wiki/Q1395022","display_name":"Convolutional code","level":3,"score":0.4301309883594513},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3508378863334656},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.27278274297714233},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.1999131739139557},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.06826618313789368},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"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.2019.2901592","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lgrs.2019.2901592","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":[{"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure","score":0.4300000071525574}],"awards":[{"id":"https://openalex.org/G1017081203","display_name":"\u57fa\u4e8e\u591a\u7279\u5f81\u8054\u5408\u7a00\u758f\u8868\u793a\u548c\u4f4e\u79e9\u5f20\u91cf\u6062\u590d\u7684\u89c6\u89c9\u8ddf\u8e2a\u7814\u7a76","funder_award_id":"61472285","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G346084562","display_name":null,"funder_award_id":"LR17F030001","funder_id":"https://openalex.org/F4320338464","funder_display_name":"Natural Science Foundation of Zhejiang Province"},{"id":"https://openalex.org/G3558139292","display_name":null,"funder_award_id":"LY17F030004","funder_id":"https://openalex.org/F4320338464","funder_display_name":"Natural Science Foundation of Zhejiang Province"},{"id":"https://openalex.org/G3779868006","display_name":null,"funder_award_id":"61503263","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4404482093","display_name":"\u9762\u5411\u9ad8\u7ef4\u5927\u6570\u636e\u7684\u534a\u76d1\u7763\u5b66\u4e60\u5173\u952e\u95ee\u9898\u7814\u7a76","funder_award_id":"61772373","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4816875984","display_name":null,"funder_award_id":"LQ18F030010","funder_id":"https://openalex.org/F4320338464","funder_display_name":"Natural Science Foundation of Zhejiang Province"},{"id":"https://openalex.org/G5226590996","display_name":"\u9762\u5411\u975e\u5bf9\u9f50\u6570\u636e\u7684\u4f4e\u79e9\u5f20\u91cf\u6062\u590d\u6a21\u578b\u53ca\u5176\u5feb\u901f\u7b97\u6cd5\u7814\u7a76","funder_award_id":"LQ19F020005","funder_id":"https://openalex.org/F4320338464","funder_display_name":"Natural Science Foundation of Zhejiang Province"},{"id":"https://openalex.org/G609213354","display_name":null,"funder_award_id":"61573356","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G682318972","display_name":null,"funder_award_id":"LY15F030011","funder_id":"https://openalex.org/F4320338464","funder_display_name":"Natural Science Foundation of Zhejiang Province"},{"id":"https://openalex.org/G6831164781","display_name":"\u57fa\u4e8e\u7ed3\u6784\u5316\u7a00\u758f\u8868\u793a\u4e0e\u6df1\u5ea6\u5b66\u4e60\u7684\u56fe\u50cf\u589e\u5f3a\u53ca\u5206\u7c7b\u6280\u672f\u7814\u7a76","funder_award_id":"61772374","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"},{"id":"https://openalex.org/F4320338464","display_name":"Natural Science Foundation of Zhejiang Province","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W1686810756","https://openalex.org/W1849277567","https://openalex.org/W1901129140","https://openalex.org/W1903029394","https://openalex.org/W1923697677","https://openalex.org/W1982872386","https://openalex.org/W2097117768","https://openalex.org/W2100588357","https://openalex.org/W2124592697","https://openalex.org/W2163605009","https://openalex.org/W2165698076","https://openalex.org/W2249740729","https://openalex.org/W2293078015","https://openalex.org/W2412782625","https://openalex.org/W2560023338","https://openalex.org/W2563705555","https://openalex.org/W2592939477","https://openalex.org/W2592962403","https://openalex.org/W2799954862","https://openalex.org/W2890732922","https://openalex.org/W2897819140","https://openalex.org/W2963840672","https://openalex.org/W2963881378","https://openalex.org/W3103856189","https://openalex.org/W3105100264","https://openalex.org/W6639204139","https://openalex.org/W6639824700","https://openalex.org/W6640295612","https://openalex.org/W6684191040"],"related_works":["https://openalex.org/W2517104666","https://openalex.org/W2005437358","https://openalex.org/W1669643531","https://openalex.org/W2008656436","https://openalex.org/W2134924024","https://openalex.org/W2023558673","https://openalex.org/W2110230079","https://openalex.org/W1982826852","https://openalex.org/W2613186388","https://openalex.org/W2295021132"],"abstract_inverted_index":{"In":[0],"this":[1],"letter,":[2],"we":[3],"propose":[4],"a":[5],"practical":[6],"convolutional":[7,33],"neural":[8],"network":[9,44,73,127],"architecture":[10,47],"for":[11],"semantic":[12],"pixelwise":[13],"segmentation":[14],"of":[15,31,39,45,51,67,83,97],"remote":[16,132],"sensing":[17,133],"images,":[18],"named":[19],"Multiscale":[20],"Decoding":[21],"Network.":[22],"The":[23,42,71],"proposed":[24,92],"method":[25,93],"is":[26,74],"built":[27],"on":[28,131],"the":[29,37,49,65,77,81,84,91,95,119],"success":[30],"fully":[32],"networks":[34,99,121],"(FCNs)":[35],"and":[36,60,80,100,114,124],"transfer":[38],"pretrained":[40,98],"networks.":[41],"decoding":[43,104],"our":[46,126],"utilizes":[48],"combination":[50],"three":[52,85,102],"paths,":[53],"namely,":[54],"unpooling":[55],"path,":[56,59,63],"transposed":[57],"convolution":[58,62],"dilated":[61],"in":[64,76],"form":[66],"an":[68],"inception":[69],"module.":[70],"whole":[72],"trained":[75],"end-to-end":[78],"manner":[79],"parameters":[82],"paths":[86,105],"are":[87],"learned":[88],"automatically.":[89],"Since":[90],"transfers":[94],"feature":[96],"has":[101],"simplified":[103],"with":[106,118],"fewer":[107],"parameters,":[108],"it":[109],"requires":[110],"less":[111],"training":[112,115],"data":[113],"time.":[116],"Compared":[117],"classical":[120],"FCN,":[122],"SegNet,":[123],"U-net,":[125],"shows":[128],"better":[129],"performance":[130],"images":[134],"segmentation.":[135]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":8},{"year":2022,"cited_by_count":10},{"year":2021,"cited_by_count":5},{"year":2020,"cited_by_count":3}],"updated_date":"2026-07-13T07:31:44.756512","created_date":"2025-10-10T00:00:00"}