{"id":"https://openalex.org/W4412837154","doi":"https://doi.org/10.1109/jstars.2025.3594605","title":"A Dense Bootstrap Contrastive Learning Method With 3-D Dynamic Convolution for Few-Shot PolSAR Image Classification","display_name":"A Dense Bootstrap Contrastive Learning Method With 3-D Dynamic Convolution for Few-Shot PolSAR Image Classification","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4412837154","doi":"https://doi.org/10.1109/jstars.2025.3594605"},"language":"en","primary_location":{"id":"doi:10.1109/jstars.2025.3594605","is_oa":true,"landing_page_url":"https://doi.org/10.1109/jstars.2025.3594605","pdf_url":null,"source":{"id":"https://openalex.org/S117727964","display_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","issn_l":"1939-1404","issn":["1939-1404","2151-1535"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1109/jstars.2025.3594605","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5083453526","display_name":"Nana Jiang","orcid":null},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Nana Jiang","raw_affiliation_strings":["School of Artificial Intelligence, Sun Yat-sen University, Zhuhai, China"],"raw_orcid":"https://orcid.org/0009-0004-1463-6955","affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, Sun Yat-sen University, Zhuhai, China","institution_ids":["https://openalex.org/I157773358"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103876174","display_name":"W L Zhao","orcid":"https://orcid.org/0009-0000-4942-1883"},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenbo Zhao","raw_affiliation_strings":["School of Artificial Intelligence, Sun Yat-sen University, Zhuhai, China"],"raw_orcid":"https://orcid.org/0009-0000-4942-1883","affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, Sun Yat-sen University, Zhuhai, China","institution_ids":["https://openalex.org/I157773358"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Jiao Guo","orcid":"https://orcid.org/0009-0003-7815-7286"},"institutions":[{"id":"https://openalex.org/I4210088176","display_name":"North West Agriculture and Forestry University","ror":null,"country_code":"CN","type":null,"lineage":["https://openalex.org/I4210088176"]},{"id":"https://openalex.org/I89652312","display_name":"Northwest A&F University","ror":"https://ror.org/0051rme32","country_code":"CN","type":"education","lineage":["https://openalex.org/I89652312"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiao Guo","raw_affiliation_strings":["College of Mechanical and Electronic Engineering, Northwest A&amp;F University, Yangling, China","College of Mechanical and Electronic Engineering, Northwest A &amp; F University, Yangling, Shanxi, China"],"raw_orcid":"https://orcid.org/0009-0003-7815-7286","affiliations":[{"raw_affiliation_string":"College of Mechanical and Electronic Engineering, Northwest A&amp;F University, Yangling, China","institution_ids":["https://openalex.org/I89652312"]},{"raw_affiliation_string":"College of Mechanical and Electronic Engineering, Northwest A &amp; F University, Yangling, Shanxi, China","institution_ids":["https://openalex.org/I4210088176"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Xiuya Dong","orcid":null},"institutions":[{"id":"https://openalex.org/I4210105385","display_name":"Shanghai Stock Exchange","ror":"https://ror.org/01ecwsw76","country_code":"CN","type":"other","lineage":["https://openalex.org/I4210105385"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiuya Dong","raw_affiliation_strings":["Shanghai Science and Technology Exchange Center, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shanghai Science and Technology Exchange Center, Shanghai, China","institution_ids":["https://openalex.org/I4210105385"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100835419","display_name":"Jubo Zhu","orcid":null},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jubo Zhu","raw_affiliation_strings":["School of Artificial Intelligence, Sun Yat-sen University, Zhuhai, China"],"raw_orcid":"https://orcid.org/0009-0003-7962-8190","affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, Sun Yat-sen University, Zhuhai, China","institution_ids":["https://openalex.org/I157773358"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":1250,"currency":"USD","value_usd":1250},"apc_paid":{"value":1250,"currency":"USD","value_usd":1250},"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.2026484,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"18","issue":null,"first_page":"20098","last_page":"20116"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11609","display_name":"Geophysical Methods and Applications","score":0.9695000052452087,"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"}},"topics":[{"id":"https://openalex.org/T11609","display_name":"Geophysical Methods and Applications","score":0.9695000052452087,"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/T11038","display_name":"Advanced SAR Imaging Techniques","score":0.9531000256538391,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace 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/T12740","display_name":"Gait Recognition and Analysis","score":0.9527999758720398,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical 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/convolution","display_name":"Convolution (computer science)","score":0.7057181000709534},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.687777042388916},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6788290739059448},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5828073620796204},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.5761761665344238},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.3896506428718567},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.11961928009986877}],"concepts":[{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.7057181000709534},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.687777042388916},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6788290739059448},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5828073620796204},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.5761761665344238},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3896506428718567},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.11961928009986877}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/jstars.2025.3594605","is_oa":true,"landing_page_url":"https://doi.org/10.1109/jstars.2025.3594605","pdf_url":null,"source":{"id":"https://openalex.org/S117727964","display_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","issn_l":"1939-1404","issn":["1939-1404","2151-1535"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:05e883135e984897a965190e935870ab","is_oa":true,"landing_page_url":"https://doaj.org/article/05e883135e984897a965190e935870ab","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 18, Pp 20098-20116 (2025)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/jstars.2025.3594605","is_oa":true,"landing_page_url":"https://doi.org/10.1109/jstars.2025.3594605","pdf_url":null,"source":{"id":"https://openalex.org/S117727964","display_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","issn_l":"1939-1404","issn":["1939-1404","2151-1535"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G3122155435","display_name":null,"funder_award_id":"U22B2015","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":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":44,"referenced_works":["https://openalex.org/W1861492603","https://openalex.org/W1903029394","https://openalex.org/W1967455454","https://openalex.org/W2108598243","https://openalex.org/W2114878155","https://openalex.org/W2132012856","https://openalex.org/W2133989913","https://openalex.org/W2141424348","https://openalex.org/W2288628559","https://openalex.org/W2345852998","https://openalex.org/W2559324447","https://openalex.org/W2740687828","https://openalex.org/W2754361766","https://openalex.org/W2930359273","https://openalex.org/W2931045221","https://openalex.org/W2946589087","https://openalex.org/W2981864880","https://openalex.org/W2984120564","https://openalex.org/W2989067579","https://openalex.org/W3031154432","https://openalex.org/W3035524453","https://openalex.org/W3114767222","https://openalex.org/W3145450063","https://openalex.org/W3159481202","https://openalex.org/W3168822201","https://openalex.org/W3171007011","https://openalex.org/W3172265425","https://openalex.org/W3174415835","https://openalex.org/W3200733355","https://openalex.org/W3206873062","https://openalex.org/W4225145356","https://openalex.org/W4290994887","https://openalex.org/W4308980428","https://openalex.org/W4312493670","https://openalex.org/W4381186552","https://openalex.org/W4387802914","https://openalex.org/W4390751375","https://openalex.org/W4391164104","https://openalex.org/W4398151425","https://openalex.org/W4399450188","https://openalex.org/W4402829793","https://openalex.org/W4405812895","https://openalex.org/W4407168447","https://openalex.org/W4412080484"],"related_works":["https://openalex.org/W4387838477","https://openalex.org/W2067193074","https://openalex.org/W2182785089","https://openalex.org/W4312178642","https://openalex.org/W2375093801","https://openalex.org/W3107426390","https://openalex.org/W1534368937","https://openalex.org/W2033914206","https://openalex.org/W2042327336","https://openalex.org/W2546503577"],"abstract_inverted_index":{"High-quality":[0],"labeled":[1,20,43,145,178],"samples":[2,21,44],"of":[3,42,86,93,149,172,177],"polarimetric":[4],"synthetic":[5],"aperture":[6],"radar":[7],"(PolSAR)":[8],"images":[9],"are":[10],"relatively":[11],"scarce.":[12],"Therefore,":[13],"achieving":[14],"optimal":[15],"classification":[16,30,51,58,71],"performance":[17],"with":[18,79],"limited":[19],"has":[22],"become":[23],"a":[24,67,107,129],"significant":[25],"challenge":[26],"in":[27,50,106],"PolSAR":[28,56,69,119],"image":[29,57,70],"tasks.":[31,59],"Existing":[32],"deep":[33],"learning":[34,78,132],"methods":[35],"not":[36],"only":[37,175],"rely":[38],"on":[39,74,157,162],"large":[40],"amounts":[41],"but":[45],"also":[46],"often":[47],"face":[48],"limitations":[49],"accuracy":[52,171],"when":[53],"handling":[54],"multi-instance":[55,118],"In":[60],"response":[61],"to":[62],"this":[63],"challenge,":[64],"we":[65,127],"propose":[66],"few-shot":[68],"method":[72,152],"based":[73],"dense":[75],"bootstrap":[76],"contrastive":[77,131],"3-dimensional":[80],"dynamic":[81],"convolution":[82],"(DBCL-3DDC).":[83],"The":[84,99,147],"design":[85,128],"3DDC":[87],"enhances":[88],"the":[89,94,124,150,163],"feature":[90,115],"extraction":[91],"ability":[92],"network":[95],"for":[96,117],"complex":[97],"data.":[98],"DBCL":[100],"learns":[101],"global":[102,138],"and":[103,109,139],"local":[104,140],"representations":[105,116,142],"30%":[108],"70%":[110],"ratio":[111],"respectively,":[112],"heuristically":[113],"extracting":[114],"images.":[120],"More":[121],"importantly,":[122],"during":[123],"pre-training":[125],"phase,":[126],"multi-level":[130],"strategy":[133],"that":[134],"fully":[135],"utilizes":[136],"both":[137],"instance":[141],"without":[143],"requiring":[144],"samples.":[146,179],"effectiveness":[148],"proposed":[151],"is":[153],"validated":[154],"through":[155],"experiments":[156],"three":[158],"different":[159],"datasets.":[160],"Notably,":[161],"Flevoland":[164],"1989":[165],"dataset,":[166],"DBCL-3DDC":[167],"achieves":[168],"an":[169],"overall":[170],"97.29%":[173],"using":[174],"0.2%":[176]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-08-02T00:00:00"}
