{"id":"https://openalex.org/W4402261994","doi":"https://doi.org/10.1109/igarss53475.2024.10642926","title":"Self-Training and Curriculum Learning Guided Dynamic Refined Network for Remote Sensing Class-Incremental Semantic Segmentation","display_name":"Self-Training and Curriculum Learning Guided Dynamic Refined Network for Remote Sensing Class-Incremental Semantic Segmentation","publication_year":2024,"publication_date":"2024-07-07","ids":{"openalex":"https://openalex.org/W4402261994","doi":"https://doi.org/10.1109/igarss53475.2024.10642926"},"language":"en","primary_location":{"id":"doi:10.1109/igarss53475.2024.10642926","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss53475.2024.10642926","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium","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/A5011270130","display_name":"Hongbo Zhao","orcid":"https://orcid.org/0000-0002-1196-4089"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hongbo Zhao","raw_affiliation_strings":["Beihang University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beihang University","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102500969","display_name":"Ruimin Ren","orcid":null},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ruimin Ren","raw_affiliation_strings":["Beihang University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beihang University","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5029244560","display_name":"Shuchang Lyu","orcid":"https://orcid.org/0000-0001-9769-7083"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shuchang Lyu","raw_affiliation_strings":["Beihang University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beihang University","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5052052722","display_name":"Binghao Liu","orcid":"https://orcid.org/0000-0001-6590-0016"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Binghao Liu","raw_affiliation_strings":["Beihang University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beihang University","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100710371","display_name":"Chunlei Wang","orcid":"https://orcid.org/0000-0002-8955-9964"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chunlei Wang","raw_affiliation_strings":["Beihang University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beihang University","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5008131938","display_name":"Meng Li","orcid":"https://orcid.org/0000-0002-7095-0170"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Meng Li","raw_affiliation_strings":["Beihang University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beihang University","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5115599767","display_name":"Guangliang Cheng","orcid":"https://orcid.org/0000-0001-8686-9513"},"institutions":[{"id":"https://openalex.org/I146655781","display_name":"University of Liverpool","ror":"https://ror.org/04xs57h96","country_code":"GB","type":"education","lineage":["https://openalex.org/I146655781"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Guangliang Cheng","raw_affiliation_strings":["University of Liverpool"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Liverpool","institution_ids":["https://openalex.org/I146655781"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101722127","display_name":"Qi Zhao","orcid":"https://orcid.org/0000-0002-3508-027X"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qi Zhao","raw_affiliation_strings":["Beihang University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beihang University","institution_ids":["https://openalex.org/I82880672"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"8334","last_page":"8338"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9955000281333923,"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":0.9955000281333923,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9855999946594238,"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"}},{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9728999733924866,"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":0.771821141242981},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6561756134033203},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.6517621278762817},{"id":"https://openalex.org/keywords/curriculum","display_name":"Curriculum","score":0.6325505971908569},{"id":"https://openalex.org/keywords/training","display_name":"Training (meteorology)","score":0.5954273343086243},{"id":"https://openalex.org/keywords/incremental-learning","display_name":"Incremental learning","score":0.5803301930427551},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5708206295967102},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4660673439502716},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.07640436291694641},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.06587201356887817}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.771821141242981},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6561756134033203},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.6517621278762817},{"id":"https://openalex.org/C47177190","wikidata":"https://www.wikidata.org/wiki/Q207137","display_name":"Curriculum","level":2,"score":0.6325505971908569},{"id":"https://openalex.org/C2777211547","wikidata":"https://www.wikidata.org/wiki/Q17141490","display_name":"Training (meteorology)","level":2,"score":0.5954273343086243},{"id":"https://openalex.org/C2780735816","wikidata":"https://www.wikidata.org/wiki/Q28324931","display_name":"Incremental learning","level":2,"score":0.5803301930427551},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5708206295967102},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4660673439502716},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.07640436291694641},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.06587201356887817},{"id":"https://openalex.org/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","level":1,"score":0.0},{"id":"https://openalex.org/C19417346","wikidata":"https://www.wikidata.org/wiki/Q7922","display_name":"Pedagogy","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/igarss53475.2024.10642926","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss53475.2024.10642926","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Quality Education","score":0.4699999988079071,"id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W2787091153","https://openalex.org/W2804199516","https://openalex.org/W2955058313","https://openalex.org/W3017361373","https://openalex.org/W3034435444","https://openalex.org/W3138136606","https://openalex.org/W3171888599","https://openalex.org/W3187986157","https://openalex.org/W3211490618","https://openalex.org/W3212231438","https://openalex.org/W4206158284","https://openalex.org/W4214893857","https://openalex.org/W4226462473","https://openalex.org/W4312693141","https://openalex.org/W4318149001","https://openalex.org/W4385062313","https://openalex.org/W4392173735","https://openalex.org/W6763251565","https://openalex.org/W6797461981"],"related_works":["https://openalex.org/W230091440","https://openalex.org/W2233261550","https://openalex.org/W2810751659","https://openalex.org/W258997015","https://openalex.org/W2997094352","https://openalex.org/W3216976533","https://openalex.org/W100620283","https://openalex.org/W2495260952","https://openalex.org/W4366179611","https://openalex.org/W2996078371"],"abstract_inverted_index":{"Class-incremental":[0],"semantic":[1],"segmentation":[2,7],"aims":[3],"to":[4,100,114],"update":[5],"the":[6,64,102,116,129,145,157],"model":[8],"with":[9],"training":[10,73],"samples":[11],"containing":[12],"only":[13],"novel":[14],"categories.":[15],"Within":[16],"this":[17],"domain,":[18],"catastrophic":[19,44,105],"forgetting":[20],"is":[21,56,67],"a":[22,36,57,82,97,110],"common":[23],"challenge.":[24],"In":[25],"remote":[26],"sensing":[27],"scenes,":[28],"images":[29],"always":[30],"have":[31],"large":[32,37],"discrepancies":[33],"caused":[34],"by":[35],"variety":[38],"of":[39,104],"geographical":[40],"objects.":[41],"Therefore,":[42],"besides":[43],"forgetting,":[45],"there":[46],"exists":[47],"two":[48],"additional":[49],"primary":[50],"challenges":[51],"persist.":[52],"The":[53],"first":[54,95],"one":[55,66],"huge":[58],"imbalance":[59],"in":[60],"image":[61],"categories":[62],"while":[63],"second":[65],"error":[68],"accumulation":[69],"during":[70],"multiple":[71],"incremental":[72],"steps.":[74],"To":[75],"solve":[76],"these":[77],"three":[78],"problems,":[79],"we":[80,94,126],"propose":[81],"new":[83,149],"Self-Training":[84],"and":[85,141,153],"Curriculum":[86],"Learning":[87],"Guided":[88],"Dynamic":[89],"Refined":[90],"Network":[91],"(STCL-DRNet).":[92],"Specifically,":[93],"design":[96,109],"self-training-based":[98],"branch":[99],"ease":[101],"tendency":[103],"forgetting.":[106],"We":[107],"then":[108],"dynamic":[111],"refined":[112],"loss":[113],"mitigate":[115],"uneven":[117],"category":[118],"distribution.":[119],"Through":[120],"further":[121,155],"embedding":[122],"class-balanced":[123],"curriculum":[124],"learning,":[125],"can":[127],"alleviate":[128],"performance":[130],"drop":[131],"from":[132],"noisy":[133],"accumulation.":[134],"Extensive":[135],"experiments":[136],"on":[137],"benchmark":[138],"datasets,":[139],"DeepGLobe":[140],"iSAID,":[142],"prove":[143],"that":[144],"proposed":[146],"STCL-DRNet":[147],"achieves":[148],"SOTA":[150],"performance.":[151],"Visualization":[152],"analysis":[154],"substantiate":[156],"interpretability.":[158]},"counts_by_year":[{"year":2025,"cited_by_count":2}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
