{"id":"https://openalex.org/W4321488352","doi":"https://doi.org/10.1109/tgrs.2023.3248040","title":"Few-Shot Class-Incremental SAR Target Recognition Based on Hierarchical Embedding and Incremental Evolutionary Network","display_name":"Few-Shot Class-Incremental SAR Target Recognition Based on Hierarchical Embedding and Incremental Evolutionary Network","publication_year":2023,"publication_date":"2023-01-01","ids":{"openalex":"https://openalex.org/W4321488352","doi":"https://doi.org/10.1109/tgrs.2023.3248040"},"language":"en","primary_location":{"id":"doi:10.1109/tgrs.2023.3248040","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2023.3248040","pdf_url":null,"source":{"id":"https://openalex.org/S111326731","display_name":"IEEE Transactions on Geoscience and Remote Sensing","issn_l":"0196-2892","issn":["0196-2892","1558-0644"],"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 Transactions on Geoscience and Remote Sensing","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/A5072148680","display_name":"Li Wang","orcid":"https://orcid.org/0000-0002-1815-5225"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Li Wang","raw_affiliation_strings":["Ministry of Education, Key Laboratory of Electronic Information Countermeasure and Simulation, Xidian University, Xi&#x2019;an, China"],"affiliations":[{"raw_affiliation_string":"Ministry of Education, Key Laboratory of Electronic Information Countermeasure and Simulation, Xidian University, Xi&#x2019;an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101484751","display_name":"Xinyao Yang","orcid":"https://orcid.org/0000-0002-7014-4195"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xinyao Yang","raw_affiliation_strings":["Ministry of Education, Key Laboratory of Electronic Information Countermeasure and Simulation, Xidian University, Xi&#x2019;an, China"],"affiliations":[{"raw_affiliation_string":"Ministry of Education, Key Laboratory of Electronic Information Countermeasure and Simulation, Xidian University, Xi&#x2019;an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101941620","display_name":"Haoyue Tan","orcid":"https://orcid.org/0009-0000-4987-6909"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haoyue Tan","raw_affiliation_strings":["Ministry of Education, Key Laboratory of Electronic Information Countermeasure and Simulation, Xidian University, Xi&#x2019;an, China"],"affiliations":[{"raw_affiliation_string":"Ministry of Education, Key Laboratory of Electronic Information Countermeasure and Simulation, Xidian University, Xi&#x2019;an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076901636","display_name":"Xueru Bai","orcid":"https://orcid.org/0000-0001-9283-1810"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xueru Bai","raw_affiliation_strings":["National Laboratory of Radar Signal Processing, Xidian University, Xi&#x2019;an, China"],"affiliations":[{"raw_affiliation_string":"National Laboratory of Radar Signal Processing, Xidian University, Xi&#x2019;an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5080509511","display_name":"Feng Zhou","orcid":"https://orcid.org/0000-0002-1514-7393"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Feng Zhou","raw_affiliation_strings":["Ministry of Education, Key Laboratory of Electronic Information Countermeasure and Simulation, Xidian University, Xi&#x2019;an, China"],"affiliations":[{"raw_affiliation_string":"Ministry of Education, Key Laboratory of Electronic Information Countermeasure and Simulation, Xidian University, Xi&#x2019;an, China","institution_ids":["https://openalex.org/I149594827"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5072148680"],"corresponding_institution_ids":["https://openalex.org/I149594827"],"apc_list":null,"apc_paid":null,"fwci":34.7371,"has_fulltext":false,"cited_by_count":42,"citation_normalized_percentile":{"value":0.99674689,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":"61","issue":null,"first_page":"1","last_page":"11"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11038","display_name":"Advanced SAR Imaging Techniques","score":0.9984999895095825,"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"}},"topics":[{"id":"https://openalex.org/T11038","display_name":"Advanced SAR Imaging Techniques","score":0.9984999895095825,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9923999905586243,"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/T12676","display_name":"Machine Learning and ELM","score":0.9613999724388123,"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/automatic-target-recognition","display_name":"Automatic target recognition","score":0.8315343260765076},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8023606538772583},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.738787055015564},{"id":"https://openalex.org/keywords/overfitting","display_name":"Overfitting","score":0.7131993174552917},{"id":"https://openalex.org/keywords/synthetic-aperture-radar","display_name":"Synthetic aperture radar","score":0.7055849432945251},{"id":"https://openalex.org/keywords/incremental-learning","display_name":"Incremental learning","score":0.5727649927139282},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5708297491073608},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.5174556374549866},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5030071139335632},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5024373531341553},{"id":"https://openalex.org/keywords/target-acquisition","display_name":"Target acquisition","score":0.49174073338508606},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.47263237833976746},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.441141813993454},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.4362648129463196},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.41342487931251526},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.35384368896484375},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.18785545229911804}],"concepts":[{"id":"https://openalex.org/C117623542","wikidata":"https://www.wikidata.org/wiki/Q621974","display_name":"Automatic target recognition","level":3,"score":0.8315343260765076},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8023606538772583},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.738787055015564},{"id":"https://openalex.org/C22019652","wikidata":"https://www.wikidata.org/wiki/Q331309","display_name":"Overfitting","level":3,"score":0.7131993174552917},{"id":"https://openalex.org/C87360688","wikidata":"https://www.wikidata.org/wiki/Q740686","display_name":"Synthetic aperture radar","level":2,"score":0.7055849432945251},{"id":"https://openalex.org/C2780735816","wikidata":"https://www.wikidata.org/wiki/Q28324931","display_name":"Incremental learning","level":2,"score":0.5727649927139282},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5708297491073608},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.5174556374549866},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5030071139335632},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5024373531341553},{"id":"https://openalex.org/C2779726219","wikidata":"https://www.wikidata.org/wiki/Q7685884","display_name":"Target acquisition","level":2,"score":0.49174073338508606},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.47263237833976746},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.441141813993454},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.4362648129463196},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.41342487931251526},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.35384368896484375},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.18785545229911804},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tgrs.2023.3248040","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2023.3248040","pdf_url":null,"source":{"id":"https://openalex.org/S111326731","display_name":"IEEE Transactions on Geoscience and Remote Sensing","issn_l":"0196-2892","issn":["0196-2892","1558-0644"],"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 Transactions on Geoscience and Remote Sensing","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5699999928474426,"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16"}],"awards":[{"id":"https://openalex.org/G1134163743","display_name":null,"funder_award_id":"62001350","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2630173159","display_name":null,"funder_award_id":"61971332","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5344939901","display_name":null,"funder_award_id":"XJS210210","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"},{"id":"https://openalex.org/G6875704605","display_name":null,"funder_award_id":"61801344","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7351667165","display_name":null,"funder_award_id":"61801347","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7996373070","display_name":null,"funder_award_id":"61631019","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8494510999","display_name":null,"funder_award_id":"XJS220211","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":38,"referenced_works":["https://openalex.org/W1682403713","https://openalex.org/W2115733720","https://openalex.org/W2187089797","https://openalex.org/W2410591237","https://openalex.org/W2473930607","https://openalex.org/W2519882289","https://openalex.org/W2554616628","https://openalex.org/W2560647685","https://openalex.org/W2883279772","https://openalex.org/W2914204846","https://openalex.org/W2948734064","https://openalex.org/W2963078860","https://openalex.org/W2963350370","https://openalex.org/W3004711070","https://openalex.org/W3012255272","https://openalex.org/W3013325675","https://openalex.org/W3035342403","https://openalex.org/W3035370595","https://openalex.org/W3113584014","https://openalex.org/W3121583704","https://openalex.org/W3131740536","https://openalex.org/W3176779063","https://openalex.org/W3177494822","https://openalex.org/W3213042253","https://openalex.org/W4205385989","https://openalex.org/W4226113955","https://openalex.org/W4226134030","https://openalex.org/W4312327301","https://openalex.org/W4312572119","https://openalex.org/W4312865701","https://openalex.org/W4385245566","https://openalex.org/W6736057607","https://openalex.org/W6738602802","https://openalex.org/W6741217325","https://openalex.org/W6743661861","https://openalex.org/W6745537798","https://openalex.org/W6755365793","https://openalex.org/W6788840927"],"related_works":["https://openalex.org/W1965572316","https://openalex.org/W4390678388","https://openalex.org/W2112220318","https://openalex.org/W2131815970","https://openalex.org/W2006284743","https://openalex.org/W3094709941","https://openalex.org/W3014874275","https://openalex.org/W2262462480","https://openalex.org/W2003904372","https://openalex.org/W4321488352"],"abstract_inverted_index":{"It":[0],"is":[1,70,108,134],"difficult":[2],"to":[3,35,49,96,110,126,136],"realize":[4],"effective":[5,138],"synthetic":[6],"aperture":[7],"radar":[8],"(SAR)":[9],"automatic":[10],"target":[11,153],"recognition":[12,156],"(ATR)":[13],"in":[14,72,94,116,170],"open":[15],"scenarios":[16],"because":[17],"the":[18,36,40,112,124,127,149],"ATR":[19,60,174],"model":[20,139],"cannot":[21],"continuously":[22],"learn":[23],"from":[24,123],"new":[25,33],"classes":[26,34,45],"with":[27,141,167],"limited":[28],"training":[29,132,140],"samples.":[30,145],"When":[31],"adding":[32],"previously":[37],"trained":[38],"model,":[39],"capability":[41],"of":[42,114],"recognizing":[43],"old":[44],"may":[46],"lose":[47],"due":[48],"severe":[50],"overfitting.":[51],"To":[52],"tackle":[53],"this":[54,73],"problem,":[55],"a":[56,76,81,130,143],"few-shot":[57,171],"class-incremental":[58,104,172],"SAR":[59,173],"method,":[61],"namely,":[62],"hierarchical":[63,77],"embedding":[64,78],"and":[65,80,91,151,155],"incremental":[66],"evolutionary":[67],"network":[68,79],"(HEIEN),":[69],"proposed":[71],"article.":[74],"First,":[75],"hybrid":[82],"distance-based":[83],"classifier":[84],"are":[85],"constructed":[86],"for":[87],"basic":[88],"feature":[89],"extraction":[90],"classification.":[92],"Then,":[93],"order":[95],"obtain":[97],"more":[98],"accurate":[99],"decision":[100],"boundaries,":[101],"an":[102],"adaptive":[103],"learning":[105],"(ACIL)":[106],"module":[107],"designed":[109,135],"adjust":[111],"weights":[113],"classifiers":[115],"all":[117],"tasks":[118],"by":[119],"collecting":[120],"context":[121],"information":[122],"past":[125],"present.":[128],"Finally,":[129],"pseudo-incremental":[131],"strategy":[133],"enable":[137],"only":[142],"few":[144],"Experimental":[146],"results":[147],"on":[148],"moving":[150],"stationary":[152],"acquisition":[154],"(MSTAR)":[157],"benchmark":[158],"data":[159],"set":[160],"have":[161],"illustrated":[162],"that":[163],"HEIEN":[164],"performs":[165],"well":[166],"remarkable":[168],"advantages":[169],"tasks.":[175]},"counts_by_year":[{"year":2025,"cited_by_count":11},{"year":2024,"cited_by_count":21},{"year":2023,"cited_by_count":10}],"updated_date":"2026-04-02T15:55:50.835912","created_date":"2025-10-10T00:00:00"}
