{"id":"https://openalex.org/W4416249447","doi":"https://doi.org/10.1109/ijcnn64981.2025.11227864","title":"DSF-Net: Dual-Path Spatial Attention Feature Fusion Network For Building Extraction From Remote Sensing Images","display_name":"DSF-Net: Dual-Path Spatial Attention Feature Fusion Network For Building Extraction From Remote Sensing Images","publication_year":2025,"publication_date":"2025-06-30","ids":{"openalex":"https://openalex.org/W4416249447","doi":"https://doi.org/10.1109/ijcnn64981.2025.11227864"},"language":null,"primary_location":{"id":"doi:10.1109/ijcnn64981.2025.11227864","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn64981.2025.11227864","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5009656753","display_name":"Changjiang Hu","orcid":"https://orcid.org/0000-0003-1909-1128"},"institutions":[{"id":"https://openalex.org/I1297991670","display_name":"Southwest University of Science and Technology","ror":"https://ror.org/04d996474","country_code":"CN","type":"education","lineage":["https://openalex.org/I1297991670"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Changjiang Hu","raw_affiliation_strings":["Southwest University of Science and Technology,Mianyang,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Southwest University of Science and Technology,Mianyang,China","institution_ids":["https://openalex.org/I1297991670"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5001999714","display_name":"Minxian Liu","orcid":null},"institutions":[{"id":"https://openalex.org/I1297991670","display_name":"Southwest University of Science and Technology","ror":"https://ror.org/04d996474","country_code":"CN","type":"education","lineage":["https://openalex.org/I1297991670"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Minxian Liu","raw_affiliation_strings":["Southwest University of Science and Technology,Mianyang,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Southwest University of Science and Technology,Mianyang,China","institution_ids":["https://openalex.org/I1297991670"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100771361","display_name":"Li Dong","orcid":"https://orcid.org/0000-0003-2002-8249"},"institutions":[{"id":"https://openalex.org/I1297991670","display_name":"Southwest University of Science and Technology","ror":"https://ror.org/04d996474","country_code":"CN","type":"education","lineage":["https://openalex.org/I1297991670"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dong Li","raw_affiliation_strings":["Southwest University of Science and Technology,Mianyang,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Southwest University of Science and Technology,Mianyang,China","institution_ids":["https://openalex.org/I1297991670"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I1297991670"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.7576000094413757,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.7576000094413757,"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":0.14869999885559082,"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/T13282","display_name":"Automated Road and Building Extraction","score":0.01759999990463257,"subfield":{"id":"https://openalex.org/subfields/2212","display_name":"Ocean Engineering"},"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/feature","display_name":"Feature (linguistics)","score":0.644599974155426},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.6378999948501587},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6079000234603882},{"id":"https://openalex.org/keywords/spatial-analysis","display_name":"Spatial analysis","score":0.4674000144004822},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.4666999876499176},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4650999903678894},{"id":"https://openalex.org/keywords/attention-network","display_name":"Attention network","score":0.46129998564720154},{"id":"https://openalex.org/keywords/aerial-image","display_name":"Aerial image","score":0.43939998745918274}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7286999821662903},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6980000138282776},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.644599974155426},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.6378999948501587},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6079000234603882},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.5264999866485596},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5027999877929688},{"id":"https://openalex.org/C159620131","wikidata":"https://www.wikidata.org/wiki/Q1938983","display_name":"Spatial analysis","level":2,"score":0.4674000144004822},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.4666999876499176},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4650999903678894},{"id":"https://openalex.org/C2993807640","wikidata":"https://www.wikidata.org/wiki/Q103709453","display_name":"Attention network","level":2,"score":0.46129998564720154},{"id":"https://openalex.org/C2776429412","wikidata":"https://www.wikidata.org/wiki/Q4688011","display_name":"Aerial image","level":3,"score":0.43939998745918274},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.42890000343322754},{"id":"https://openalex.org/C69744172","wikidata":"https://www.wikidata.org/wiki/Q860822","display_name":"Image fusion","level":3,"score":0.390500009059906},{"id":"https://openalex.org/C183365957","wikidata":"https://www.wikidata.org/wiki/Q17140402","display_name":"Remote sensing application","level":3,"score":0.36880001425743103},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.32519999146461487},{"id":"https://openalex.org/C2983787585","wikidata":"https://www.wikidata.org/wiki/Q93586","display_name":"Feature matching","level":3,"score":0.3197999894618988},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.3181000053882599},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.31790000200271606},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.289000004529953},{"id":"https://openalex.org/C2986522900","wikidata":"https://www.wikidata.org/wiki/Q2178623","display_name":"Spatial relationship","level":2,"score":0.2831000089645386},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.27790001034736633},{"id":"https://openalex.org/C126422989","wikidata":"https://www.wikidata.org/wiki/Q93586","display_name":"Feature detection (computer vision)","level":4,"score":0.2750000059604645},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.2623000144958496}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn64981.2025.11227864","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn64981.2025.11227864","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 International Joint Conference on Neural Networks (IJCNN)","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":13,"referenced_works":["https://openalex.org/W1903029394","https://openalex.org/W2609402060","https://openalex.org/W2787091153","https://openalex.org/W3211490618","https://openalex.org/W4226289601","https://openalex.org/W4312443924","https://openalex.org/W4319157933","https://openalex.org/W4321232185","https://openalex.org/W4383118053","https://openalex.org/W4385859309","https://openalex.org/W4386160455","https://openalex.org/W4403067249","https://openalex.org/W4403944333"],"related_works":[],"abstract_inverted_index":{"Building":[0],"extraction":[1],"from":[2,8],"remote":[3,155],"sensing":[4,156],"images":[5],"often":[6],"suffers":[7],"the":[9,74,90,120,129],"loss":[10],"of":[11,20,76,92,131,136],"spatial":[12,22,56,81],"dependencies":[13],"among":[14],"buildings":[15],"due":[16],"to":[17,72,142],"insufficient":[18],"consideration":[19],"local-global":[21],"feature":[23,85,93,97],"correlations.":[24],"This":[25],"limitation":[26],"frequently":[27],"results":[28],"in":[29],"blurred":[30],"boundaries,":[31],"unclear":[32],"segmentation,":[33],"or":[34],"disorganized":[35],"outputs.":[36],"To":[37,87],"address":[38],"these":[39],"challenges,":[40],"we":[41],"propose":[42],"a":[43,64,102],"Dual-Path":[44,65],"Spatial":[45,66],"Attention":[46,67],"Feature":[47,68],"Fusion":[48,69],"Network":[49],"(DSF-Net)":[50],"that":[51],"combines":[52],"CNN":[53],"and":[54,79,95,111,123,138],"Transformer-based":[55],"attention":[57,110,113],"mechanisms.":[58],"At":[59],"its":[60,152],"core,":[61],"DSF-Net":[62,146],"employs":[63],"(DAFF)":[70],"module":[71],"enhance":[73],"analysis":[75],"detailed":[77],"local":[78],"global":[80],"features,":[82],"enabling":[83],"comprehensive":[84],"integration.":[86],"further":[88],"improve":[89],"accuracy":[91],"interactions":[94],"strengthen":[96],"representations":[98],"for":[99,154],"effective":[100],"alignment,":[101],"Features":[103],"Alignment":[104],"Module":[105],"(FAM)":[106],"based":[107],"on":[108,119],"Transformer":[109],"channel":[112],"mechanisms":[114],"is":[115],"introduced.":[116],"Experimental":[117],"evaluations":[118],"Massachusetts":[121],"Buildings":[122],"Inria":[124],"Aerial":[125],"Image":[126],"datasets":[127],"demonstrate":[128],"effectiveness":[130],"DSF-Net,":[132],"achieving":[133],"IoU":[134],"scores":[135],"76.56%":[137],"83.36%,":[139],"respectively.":[140],"Compared":[141],"state-of-the-art":[143],"segmentation":[144,149],"networks,":[145],"offers":[147],"superior":[148],"performance,":[150],"underscoring":[151],"potential":[153],"applications.":[157]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-11-14T00:00:00"}