{"id":"https://openalex.org/W4296211159","doi":"https://doi.org/10.1109/lgrs.2022.3207465","title":"Pixel-Level Self-Supervised Learning for Semi-Supervised Building Extraction From Remote Sensing Images","display_name":"Pixel-Level Self-Supervised Learning for Semi-Supervised Building Extraction From Remote Sensing Images","publication_year":2022,"publication_date":"2022-01-01","ids":{"openalex":"https://openalex.org/W4296211159","doi":"https://doi.org/10.1109/lgrs.2022.3207465"},"language":"en","primary_location":{"id":"doi:10.1109/lgrs.2022.3207465","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lgrs.2022.3207465","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/A5069652653","display_name":"Anzhu Yu","orcid":"https://orcid.org/0000-0002-3332-9668"},"institutions":[{"id":"https://openalex.org/I169689159","display_name":"PLA Information Engineering University","ror":"https://ror.org/00mm1qk40","country_code":"CN","type":"education","lineage":["https://openalex.org/I169689159"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Anzhu Yu","raw_affiliation_strings":["School of Surveying and Mapping, PLA Strategic Support Force Information Engineering University, Zhengzhou, China"],"raw_orcid":"https://orcid.org/0000-0002-3332-9668","affiliations":[{"raw_affiliation_string":"School of Surveying and Mapping, PLA Strategic Support Force Information Engineering University, Zhengzhou, China","institution_ids":["https://openalex.org/I169689159"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5039991862","display_name":"Bing Liu","orcid":"https://orcid.org/0000-0003-0848-8453"},"institutions":[{"id":"https://openalex.org/I169689159","display_name":"PLA Information Engineering University","ror":"https://ror.org/00mm1qk40","country_code":"CN","type":"education","lineage":["https://openalex.org/I169689159"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bing Liu","raw_affiliation_strings":["School of Surveying and Mapping, PLA Strategic Support Force Information Engineering University, Zhengzhou, China"],"raw_orcid":"https://orcid.org/0000-0003-0848-8453","affiliations":[{"raw_affiliation_string":"School of Surveying and Mapping, PLA Strategic Support Force Information Engineering University, Zhengzhou, China","institution_ids":["https://openalex.org/I169689159"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101398948","display_name":"Xuefeng Cao","orcid":"https://orcid.org/0000-0003-0529-3538"},"institutions":[{"id":"https://openalex.org/I169689159","display_name":"PLA Information Engineering University","ror":"https://ror.org/00mm1qk40","country_code":"CN","type":"education","lineage":["https://openalex.org/I169689159"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xuefeng Cao","raw_affiliation_strings":["School of Surveying and Mapping, PLA Strategic Support Force Information Engineering University, Zhengzhou, China"],"raw_orcid":"https://orcid.org/0000-0003-0529-3538","affiliations":[{"raw_affiliation_string":"School of Surveying and Mapping, PLA Strategic Support Force Information Engineering University, Zhengzhou, China","institution_ids":["https://openalex.org/I169689159"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5072647192","display_name":"Chunping Qiu","orcid":"https://orcid.org/0000-0002-7109-5559"},"institutions":[{"id":"https://openalex.org/I169689159","display_name":"PLA Information Engineering University","ror":"https://ror.org/00mm1qk40","country_code":"CN","type":"education","lineage":["https://openalex.org/I169689159"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chunping Qiu","raw_affiliation_strings":["School of Surveying and Mapping, PLA Strategic Support Force Information Engineering University, Zhengzhou, China"],"raw_orcid":"https://orcid.org/0000-0002-7109-5559","affiliations":[{"raw_affiliation_string":"School of Surveying and Mapping, PLA Strategic Support Force Information Engineering University, Zhengzhou, China","institution_ids":["https://openalex.org/I169689159"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5042512723","display_name":"Wenyue Guo","orcid":"https://orcid.org/0000-0002-5538-7535"},"institutions":[{"id":"https://openalex.org/I169689159","display_name":"PLA Information Engineering University","ror":"https://ror.org/00mm1qk40","country_code":"CN","type":"education","lineage":["https://openalex.org/I169689159"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenyue Guo","raw_affiliation_strings":["School of Surveying and Mapping, PLA Strategic Support Force Information Engineering University, Zhengzhou, China"],"raw_orcid":"https://orcid.org/0000-0002-5538-7535","affiliations":[{"raw_affiliation_string":"School of Surveying and Mapping, PLA Strategic Support Force Information Engineering University, Zhengzhou, China","institution_ids":["https://openalex.org/I169689159"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5068443980","display_name":"Yujun Quan","orcid":"https://orcid.org/0000-0001-6438-4515"},"institutions":[{"id":"https://openalex.org/I169689159","display_name":"PLA Information Engineering University","ror":"https://ror.org/00mm1qk40","country_code":"CN","type":"education","lineage":["https://openalex.org/I169689159"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yujun Quan","raw_affiliation_strings":["School of Surveying and Mapping, PLA Strategic Support Force Information Engineering University, Zhengzhou, China"],"raw_orcid":"https://orcid.org/0000-0001-6438-4515","affiliations":[{"raw_affiliation_string":"School of Surveying and Mapping, PLA Strategic Support Force Information Engineering University, Zhengzhou, China","institution_ids":["https://openalex.org/I169689159"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I169689159"],"apc_list":null,"apc_paid":null,"fwci":0.8779,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.76344086,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":98},"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/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/T13282","display_name":"Automated Road and Building Extraction","score":0.9969000220298767,"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"}},{"id":"https://openalex.org/T13890","display_name":"Remote Sensing and Land Use","score":0.9944000244140625,"subfield":{"id":"https://openalex.org/subfields/1902","display_name":"Atmospheric Science"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8251329660415649},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7298348546028137},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.6265163421630859},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5748062133789062},{"id":"https://openalex.org/keywords/supervised-learning","display_name":"Supervised learning","score":0.5606001019477844},{"id":"https://openalex.org/keywords/intersection","display_name":"Intersection (aeronautics)","score":0.5570952892303467},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5102987289428711},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.49044176936149597},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.48257508873939514},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4551042318344116},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.20284229516983032}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8251329660415649},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7298348546028137},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.6265163421630859},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5748062133789062},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.5606001019477844},{"id":"https://openalex.org/C64543145","wikidata":"https://www.wikidata.org/wiki/Q162942","display_name":"Intersection (aeronautics)","level":2,"score":0.5570952892303467},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5102987289428711},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.49044176936149597},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.48257508873939514},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4551042318344116},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.20284229516983032},{"id":"https://openalex.org/C146978453","wikidata":"https://www.wikidata.org/wiki/Q3798668","display_name":"Aerospace engineering","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/lgrs.2022.3207465","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lgrs.2022.3207465","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":[{"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11","score":0.8500000238418579}],"awards":[{"id":"https://openalex.org/G3605115833","display_name":null,"funder_award_id":"42101458","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7420870516","display_name":null,"funder_award_id":"41801388","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G938334593","display_name":null,"funder_award_id":"42130112","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"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":31,"referenced_works":["https://openalex.org/W1901129140","https://openalex.org/W2588000623","https://openalex.org/W2615237590","https://openalex.org/W2623331213","https://openalex.org/W2755226765","https://openalex.org/W2898204262","https://openalex.org/W2908320224","https://openalex.org/W2954996726","https://openalex.org/W2982206001","https://openalex.org/W2983376237","https://openalex.org/W3002497127","https://openalex.org/W3034427230","https://openalex.org/W3035524453","https://openalex.org/W3047246571","https://openalex.org/W3088971399","https://openalex.org/W3104035745","https://openalex.org/W3104355817","https://openalex.org/W3104825134","https://openalex.org/W3123392265","https://openalex.org/W3171007011","https://openalex.org/W3172615411","https://openalex.org/W3197182108","https://openalex.org/W3212022090","https://openalex.org/W4210736635","https://openalex.org/W4313156423","https://openalex.org/W6744513255","https://openalex.org/W6755837410","https://openalex.org/W6779326418","https://openalex.org/W6794295097","https://openalex.org/W6803924480","https://openalex.org/W6841161970"],"related_works":["https://openalex.org/W2348909947","https://openalex.org/W4292672442","https://openalex.org/W2085033728","https://openalex.org/W4285411112","https://openalex.org/W2362101859","https://openalex.org/W2171299904","https://openalex.org/W2791431590","https://openalex.org/W2941610985","https://openalex.org/W4235810826","https://openalex.org/W2350688482"],"abstract_inverted_index":{"The":[0,108],"building":[1,34,57,66],"extraction":[2,35,67],"from":[3],"remote":[4,155],"sensed":[5],"images":[6,45],"ash":[7],"been":[8],"a":[9,53,65,78,99],"challenging":[10],"yet":[11],"vital":[12],"task":[13],"for":[14,56,151,154],"applicable":[15],"purposes":[16],"such":[17],"as":[18],"urban":[19],"monitoring":[20],"and":[21,46,116,131,137],"cartography.":[22],"Most":[23],"of":[24,37,83,147],"the":[25,32,39,47,62,72,93,117,145],"existing":[26],"learning":[27],"based":[28],"approaches":[29,87],"focus":[30],"on":[31,112],"supervised":[33,86,135],"methods,":[36],"which":[38,59],"models":[40],"should":[41],"be":[42],"trained":[43,76],"with":[44,77,105],"corresponding":[48],"labels.":[49],"This":[50],"research":[51],"exploits":[52],"self-supervised":[54,80,90,139,149],"approach":[55,136,150],"extraction,":[58],"could":[60],"train":[61],"backbone":[63,73,95],"within":[64],"network":[68,101],"without":[69],"annotations.":[70,107],"Specifically,":[71],"is":[74,96],"initially":[75],"pixel-level":[79,148],"module":[81],"instead":[82],"commonly":[84],"used":[85],"or":[88],"instance-level":[89,138],"modules.":[91],"Next,":[92],"pretrained":[94],"embedded":[97],"into":[98],"task-specific":[100],"followed":[102],"by":[103],"tuning":[104],"limited":[106],"experiments":[109],"were":[110],"conducted":[111],"three":[113],"popular":[114],"datasets":[115],"results":[118],"show":[119],"that":[120],"our":[121],"method":[122],"achieves":[123],"improvements":[124],"regarding":[125],"both":[126],"intersection":[127],"over":[128],"union":[129],"(IoU)":[130],"F1-score":[132],"compared":[133],"to":[134],"methods.":[140],"Our":[141],"study":[142],"thus":[143],"confirms":[144],"potential":[146],"semantic":[152],"segmentation":[153],"sensing":[156],"images.":[157]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}