{"id":"https://openalex.org/W4388720260","doi":"https://doi.org/10.1109/iecon51785.2023.10312040","title":"ULKNet:Rethinking Large Kernel CNN with UNet-Attention for Remote Sensing Images Semantic Segmentation","display_name":"ULKNet:Rethinking Large Kernel CNN with UNet-Attention for Remote Sensing Images Semantic Segmentation","publication_year":2023,"publication_date":"2023-10-16","ids":{"openalex":"https://openalex.org/W4388720260","doi":"https://doi.org/10.1109/iecon51785.2023.10312040"},"language":"en","primary_location":{"id":"doi:10.1109/iecon51785.2023.10312040","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/iecon51785.2023.10312040","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IECON 2023- 49th Annual Conference of the IEEE Industrial Electronics Society","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/A5100690571","display_name":"Weilin Liu","orcid":"https://orcid.org/0000-0003-3726-1223"},"institutions":[{"id":"https://openalex.org/I15823474","display_name":"Linyi University","ror":"https://ror.org/01knv0402","country_code":"CN","type":"education","lineage":["https://openalex.org/I15823474"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Weilin Liu","raw_affiliation_strings":["The School of Information Science, Linyi University,Linyi,China","The School of Information Science, Linyi University, Linyi, China"],"affiliations":[{"raw_affiliation_string":"The School of Information Science, Linyi University,Linyi,China","institution_ids":["https://openalex.org/I15823474"]},{"raw_affiliation_string":"The School of Information Science, Linyi University, Linyi, China","institution_ids":["https://openalex.org/I15823474"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5113047902","display_name":"Lunqian Wang","orcid":"https://orcid.org/0000-0003-1183-4740"},"institutions":[{"id":"https://openalex.org/I15823474","display_name":"Linyi University","ror":"https://ror.org/01knv0402","country_code":"CN","type":"education","lineage":["https://openalex.org/I15823474"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lunqian Wang","raw_affiliation_strings":["The School of Information Science, Linyi University,Linyi,China","The School of Information Science, Linyi University, Linyi, China"],"affiliations":[{"raw_affiliation_string":"The School of Information Science, Linyi University,Linyi,China","institution_ids":["https://openalex.org/I15823474"]},{"raw_affiliation_string":"The School of Information Science, Linyi University, Linyi, China","institution_ids":["https://openalex.org/I15823474"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074181918","display_name":"Xinghua Wang","orcid":"https://orcid.org/0000-0003-4954-8811"},"institutions":[{"id":"https://openalex.org/I15823474","display_name":"Linyi University","ror":"https://ror.org/01knv0402","country_code":"CN","type":"education","lineage":["https://openalex.org/I15823474"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xinghua Wang","raw_affiliation_strings":["The School of Information Science, Linyi University,Linyi,China","The School of Information Science, Linyi University, Linyi, China"],"affiliations":[{"raw_affiliation_string":"The School of Information Science, Linyi University,Linyi,China","institution_ids":["https://openalex.org/I15823474"]},{"raw_affiliation_string":"The School of Information Science, Linyi University, Linyi, China","institution_ids":["https://openalex.org/I15823474"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101717963","display_name":"Hao Ding","orcid":"https://orcid.org/0000-0003-4539-582X"},"institutions":[{"id":"https://openalex.org/I15823474","display_name":"Linyi University","ror":"https://ror.org/01knv0402","country_code":"CN","type":"education","lineage":["https://openalex.org/I15823474"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hao Ding","raw_affiliation_strings":["The School of Informatio Science, Linyi University,Linyi,China","The School of Informatio Science, Linyi University, Linyi, China"],"affiliations":[{"raw_affiliation_string":"The School of Informatio Science, Linyi University,Linyi,China","institution_ids":["https://openalex.org/I15823474"]},{"raw_affiliation_string":"The School of Informatio Science, Linyi University, Linyi, China","institution_ids":["https://openalex.org/I15823474"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5072713174","display_name":"Bo Xia","orcid":"https://orcid.org/0009-0003-3507-9732"},"institutions":[{"id":"https://openalex.org/I15823474","display_name":"Linyi University","ror":"https://ror.org/01knv0402","country_code":"CN","type":"education","lineage":["https://openalex.org/I15823474"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bo Xia","raw_affiliation_strings":["The School of Information Science, Linyi University,Linyi,China","The School of Information Science, Linyi University, Linyi, China"],"affiliations":[{"raw_affiliation_string":"The School of Information Science, Linyi University,Linyi,China","institution_ids":["https://openalex.org/I15823474"]},{"raw_affiliation_string":"The School of Information Science, Linyi University, Linyi, China","institution_ids":["https://openalex.org/I15823474"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5032089035","display_name":"Zekai Zhang","orcid":"https://orcid.org/0000-0002-1312-5828"},"institutions":[{"id":"https://openalex.org/I152269853","display_name":"Qilu University of Technology","ror":"https://ror.org/04hyzq608","country_code":"CN","type":"education","lineage":["https://openalex.org/I152269853"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zekai Zhang","raw_affiliation_strings":["Shandong Computing Center, Qilu University of Technology,Jinan,China","Shandong Computing Center, Qilu University of Technology, Jinan, China"],"affiliations":[{"raw_affiliation_string":"Shandong Computing Center, Qilu University of Technology,Jinan,China","institution_ids":["https://openalex.org/I152269853"]},{"raw_affiliation_string":"Shandong Computing Center, Qilu University of Technology, Jinan, China","institution_ids":["https://openalex.org/I152269853"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5100690571"],"corresponding_institution_ids":["https://openalex.org/I15823474"],"apc_list":null,"apc_paid":null,"fwci":0.1623,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.53270715,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":"39","issue":null,"first_page":"1","last_page":"10"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9994999766349792,"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":0.9994999766349792,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9990000128746033,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9972000122070312,"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":0.8076868057250977},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.769914984703064},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6829969882965088},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.6553532481193542},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6495898962020874},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.5793358087539673},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4717192053794861},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.41735705733299255},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.41475996375083923},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.2914188504219055}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8076868057250977},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.769914984703064},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6829969882965088},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.6553532481193542},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6495898962020874},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.5793358087539673},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4717192053794861},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.41735705733299255},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.41475996375083923},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.2914188504219055},{"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},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"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/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iecon51785.2023.10312040","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/iecon51785.2023.10312040","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IECON 2023- 49th Annual Conference of the IEEE Industrial Electronics Society","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":59,"referenced_works":["https://openalex.org/W1901129140","https://openalex.org/W2194775991","https://openalex.org/W2395611524","https://openalex.org/W2760340275","https://openalex.org/W2886934227","https://openalex.org/W2921495890","https://openalex.org/W2921526792","https://openalex.org/W2940726923","https://openalex.org/W2952809536","https://openalex.org/W2955058313","https://openalex.org/W2963091558","https://openalex.org/W2963294354","https://openalex.org/W2963890956","https://openalex.org/W2964217532","https://openalex.org/W2970773259","https://openalex.org/W2981609437","https://openalex.org/W2987761193","https://openalex.org/W2995766874","https://openalex.org/W3007268491","https://openalex.org/W3019771380","https://openalex.org/W3034971973","https://openalex.org/W3046711384","https://openalex.org/W3047725879","https://openalex.org/W3081260473","https://openalex.org/W3092462694","https://openalex.org/W3103092912","https://openalex.org/W3127751679","https://openalex.org/W3128592650","https://openalex.org/W3128776197","https://openalex.org/W3129029680","https://openalex.org/W3132401450","https://openalex.org/W3137572916","https://openalex.org/W3138516171","https://openalex.org/W3161120562","https://openalex.org/W3162977387","https://openalex.org/W3167976421","https://openalex.org/W3169745417","https://openalex.org/W3169865585","https://openalex.org/W3170841864","https://openalex.org/W3177272171","https://openalex.org/W3196691776","https://openalex.org/W3196904463","https://openalex.org/W3201623325","https://openalex.org/W3214821343","https://openalex.org/W4200547174","https://openalex.org/W4212774754","https://openalex.org/W4213200979","https://openalex.org/W4214893857","https://openalex.org/W4226334005","https://openalex.org/W4283450732","https://openalex.org/W4299802238","https://openalex.org/W4313159166","https://openalex.org/W4321232185","https://openalex.org/W4385245566","https://openalex.org/W6640054144","https://openalex.org/W6790019176","https://openalex.org/W6791776128","https://openalex.org/W6797399245","https://openalex.org/W6800217721"],"related_works":["https://openalex.org/W4293226380","https://openalex.org/W4321487865","https://openalex.org/W2964954556","https://openalex.org/W3034421924","https://openalex.org/W2982536526","https://openalex.org/W4386858688","https://openalex.org/W4380302312","https://openalex.org/W4390971171","https://openalex.org/W4385338604","https://openalex.org/W3081626085"],"abstract_inverted_index":{"Since":[0],"the":[1,4,6,13,50,59,104,110],"advent":[2],"of":[3],"Transformer,":[5],"Vision":[7],"Transformer":[8],"(ViT)":[9],"model":[10],"has":[11,30],"become":[12],"optimal":[14],"solution":[15],"for":[16],"extracting":[17,147],"semantic":[18,24,82,148],"information":[19,40,83],"in":[20,77],"remote":[21],"sensing":[22],"image":[23],"segmentation":[25],"tasks.":[26],"However,":[27],"recent":[28],"research":[29],"discovered":[31],"that":[32,99,128],"using":[33],"larger":[34,139],"convolutional":[35,60],"kernels":[36],"to":[37,57,79,103],"extract":[38,81],"global":[39],"can":[41,136],"achieve":[42,118],"performance":[43,101],"comparable":[44,102],"to,":[45],"or":[46],"even":[47],"better":[48,80,146],"than":[49],"ViT":[51,105],"models.":[52],"This":[53,125],"finding":[54,126],"inspires":[55],"us":[56],"redesign":[58],"neural":[61],"network":[62,134],"structure":[63,135],"and":[64,84,113,121,140],"innovatively":[65],"construct":[66],"a":[67,95,129,138],"novel":[68],"parallel":[69],"global-local":[70],"module":[71],"based":[72],"on":[73,109],"large":[74,131],"kernel":[75,132],"convolution,":[76],"order":[78],"local":[85],"contextual":[86],"information.":[87,149],"Following":[88],"this":[89],"design":[90],"approach,":[91],"we":[92],"propose":[93],"ULKNet,":[94],"pure":[96],"CNN":[97,133],"architecture":[98],"achieves":[100],"model.":[106],"Through":[107],"experiments":[108],"ISPRS":[111],"Vaihingen":[112],"Potsdam":[114],"datasets,":[115],"We":[116],"respectively":[117],"mIoU":[119,123],"82.7%":[120],"86.0%":[122],"scores.":[124],"demonstrates":[127],"well-designed":[130],"provide":[137],"more":[141],"effective":[142],"receptive":[143],"field,":[144],"thereby":[145]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2025-12-25T23:11:45.687758","created_date":"2025-10-10T00:00:00"}