{"id":"https://openalex.org/W4315473895","doi":"https://doi.org/10.1109/tgrs.2023.3235747","title":"Generalized Ridge Regression-Based Channelwise Feature Map Weighted Reconstruction Network for Fine-Grained Few-Shot Ship Classification","display_name":"Generalized Ridge Regression-Based Channelwise Feature Map Weighted Reconstruction Network for Fine-Grained Few-Shot Ship Classification","publication_year":2023,"publication_date":"2023-01-01","ids":{"openalex":"https://openalex.org/W4315473895","doi":"https://doi.org/10.1109/tgrs.2023.3235747"},"language":"en","primary_location":{"id":"doi:10.1109/tgrs.2023.3235747","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2023.3235747","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/A5057387558","display_name":"Yangfan Li","orcid":"https://orcid.org/0000-0002-8965-7134"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210115570","display_name":"National Space Science Center","ror":"https://ror.org/02nnjtm50","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210115570"]},{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yangfan Li","raw_affiliation_strings":["Key Laboratory of Electronics and Information Technology for Space Systems, National Space Science Center, Chinese Academy of Sciences, Beijing, China","School of Computer Science and Technology, University of Chinese Academy of Sciences, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-8965-7134","affiliations":[{"raw_affiliation_string":"Key Laboratory of Electronics and Information Technology for Space Systems, National Space Science Center, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I19820366","https://openalex.org/I4210115570"]},{"raw_affiliation_string":"School of Computer Science and Technology, University of Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210165038"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5002071690","display_name":"Chunjiang Bian","orcid":"https://orcid.org/0000-0003-4867-0137"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210115570","display_name":"National Space Science Center","ror":"https://ror.org/02nnjtm50","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210115570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chunjiang Bian","raw_affiliation_strings":["Key Laboratory of Electronics and Information Technology for Space Systems, National Space Science Center, Chinese Academy of Sciences (CAS), Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Key Laboratory of Electronics and Information Technology for Space Systems, National Space Science Center, Chinese Academy of Sciences (CAS), Beijing, China","institution_ids":["https://openalex.org/I19820366","https://openalex.org/I4210115570"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101678716","display_name":"Hongzhen Chen","orcid":"https://orcid.org/0000-0002-0181-9742"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210115570","display_name":"National Space Science Center","ror":"https://ror.org/02nnjtm50","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210115570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hongzhen Chen","raw_affiliation_strings":["Key Laboratory of Electronics and Information Technology for Space Systems, National Space Science Center, Chinese Academy of Sciences (CAS), Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-0181-9742","affiliations":[{"raw_affiliation_string":"Key Laboratory of Electronics and Information Technology for Space Systems, National Space Science Center, Chinese Academy of Sciences (CAS), Beijing, China","institution_ids":["https://openalex.org/I19820366","https://openalex.org/I4210115570"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.5517,"has_fulltext":false,"cited_by_count":12,"citation_normalized_percentile":{"value":0.85317411,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":98},"biblio":{"volume":"61","issue":null,"first_page":"1","last_page":"10"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9980999827384949,"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"}},"topics":[{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9980999827384949,"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":0.9732000231742859,"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/T12676","display_name":"Machine Learning and ELM","score":0.9391000270843506,"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/discriminative-model","display_name":"Discriminative model","score":0.7197921276092529},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6960499286651611},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.6950298547744751},{"id":"https://openalex.org/keywords/ridge","display_name":"Ridge","score":0.6768330931663513},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6117643713951111},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.606698751449585},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.5379164218902588},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.509655237197876},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.46347129344940186},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.4628618657588959},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.20470774173736572},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.10366559028625488},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.09069260954856873},{"id":"https://openalex.org/keywords/cartography","display_name":"Cartography","score":0.07246121764183044}],"concepts":[{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.7197921276092529},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6960499286651611},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.6950298547744751},{"id":"https://openalex.org/C32277403","wikidata":"https://www.wikidata.org/wiki/Q740445","display_name":"Ridge","level":2,"score":0.6768330931663513},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6117643713951111},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.606698751449585},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.5379164218902588},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.509655237197876},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.46347129344940186},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.4628618657588959},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.20470774173736572},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.10366559028625488},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.09069260954856873},{"id":"https://openalex.org/C58640448","wikidata":"https://www.wikidata.org/wiki/Q42515","display_name":"Cartography","level":1,"score":0.07246121764183044},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tgrs.2023.3235747","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2023.3235747","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":[{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.6899999976158142}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":54,"referenced_works":["https://openalex.org/W1797268635","https://openalex.org/W1846799578","https://openalex.org/W2067178723","https://openalex.org/W2601450892","https://openalex.org/W2742093937","https://openalex.org/W2796346823","https://openalex.org/W2798836702","https://openalex.org/W2963070905","https://openalex.org/W2963741406","https://openalex.org/W2963943197","https://openalex.org/W2964105864","https://openalex.org/W2964112702","https://openalex.org/W2979689312","https://openalex.org/W2980347982","https://openalex.org/W2986821660","https://openalex.org/W2995589713","https://openalex.org/W3012255272","https://openalex.org/W3035143213","https://openalex.org/W3096675569","https://openalex.org/W3096805028","https://openalex.org/W3110214837","https://openalex.org/W3121583704","https://openalex.org/W3131740536","https://openalex.org/W3132437036","https://openalex.org/W3133008479","https://openalex.org/W3163623915","https://openalex.org/W3176341011","https://openalex.org/W3188824417","https://openalex.org/W3194746126","https://openalex.org/W4210884681","https://openalex.org/W4214562728","https://openalex.org/W4214725994","https://openalex.org/W4285274658","https://openalex.org/W4287121509","https://openalex.org/W4294646197","https://openalex.org/W4300860215","https://openalex.org/W4312500832","https://openalex.org/W6638677478","https://openalex.org/W6696185917","https://openalex.org/W6717697761","https://openalex.org/W6720057410","https://openalex.org/W6735236233","https://openalex.org/W6736057607","https://openalex.org/W6742288159","https://openalex.org/W6748136086","https://openalex.org/W6749327742","https://openalex.org/W6750254146","https://openalex.org/W6751655026","https://openalex.org/W6753311412","https://openalex.org/W6758126075","https://openalex.org/W6766092863","https://openalex.org/W6767471572","https://openalex.org/W6768230505","https://openalex.org/W6780975210"],"related_works":["https://openalex.org/W2965546495","https://openalex.org/W4389116644","https://openalex.org/W2153315159","https://openalex.org/W3103844505","https://openalex.org/W259157601","https://openalex.org/W4205463238","https://openalex.org/W3148196241","https://openalex.org/W1606169643","https://openalex.org/W1977912248","https://openalex.org/W3092773549"],"abstract_inverted_index":{"Fine-grained":[0],"ship":[1,35,55,217],"classification":[2,22,56,218],"(FGSCR)":[3],"has":[4,17],"many":[5],"applications":[6],"in":[7,158],"military":[8],"and":[9,24,66,199],"civilian":[10],"fields.":[11],"In":[12,58],"recent":[13],"years,":[14],"deep":[15],"learning":[16,88,207],"been":[18],"widely":[19],"used":[20,157],"for":[21,83],"tasks,":[23],"its":[25],"success":[26],"is":[27,181,225],"inseparable":[28],"from":[29],"that":[30,222],"of":[31,44,226],"big":[32],"data.":[33],"However,":[34],"images":[36,43],"are":[37],"valuable,":[38],"with":[39,75,135,203],"only":[40],"a":[41,45,97,146],"few":[42],"specific":[46],"category":[47],"being":[48],"obtained,":[49],"leading":[50],"to":[51,106,121,151],"the":[52,91,113,122,128,153,159,167,175,184,194,210,214],"fine-grained":[53,195,215],"few-shot":[54,87,206,216],"problem.":[57],"addition,":[59],"feature":[60,101,115,124,170],"map":[61,102,116,125],"channels":[62,74,92,126,134],"contain":[63],"distinct":[64,76],"characteristics":[65,77],"discriminative":[67,137],"details,":[68],"which":[69],"significantly":[70],"influence":[71],"FGSCR.":[72],"Intuitively,":[73],"should":[78],"be":[79],"assigned":[80],"larger":[81],"weights":[82,120],"classification,":[84],"but":[85],"most":[86],"methods":[89],"treat":[90],"equally.":[93],"Therefore,":[94],"we":[95,111,144,172,220],"propose":[96,145],"generalized":[98,129,160],"ridge-regression-based":[99],"channelwise":[100],"weighted":[103],"reconstruction":[104,176,179],"network":[105],"address":[107],"these":[108],"issues.":[109],"First,":[110],"reconstruct":[112],"query":[114,169],"by":[117],"assigning":[118],"different":[119],"support":[123,147],"using":[127],"ridge":[130,161],"regression":[131,162],"method.":[132,163],"The":[133,178],"large":[136],"details":[138],"contribute":[139],"more":[140],"toward":[141],"reconstruction.":[142],"Second,":[143],"channel":[148,154],"weight":[149,155],"module":[150],"calculate":[152,174],"matrix":[156],"Finally,":[164],"based":[165],"on":[166,193,213],"reconstructed":[168],"map,":[171],"can":[173],"error.":[177],"error":[180],"adopted":[182],"as":[183],"distance":[185],"metric.":[186],"Our":[187],"proposed":[188],"method":[189],"achieves":[190],"excellent":[191],"performance":[192],"ship,":[196],"bird,":[197],"aircraft,":[198],"WHU-RS19":[200],"datasets":[201],"compared":[202],"other":[204],"representative":[205],"methods.":[208],"Considering":[209],"limited":[211],"studies":[212],"problem,":[219],"believe":[221],"our":[223],"work":[224],"great":[227],"significance.":[228]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":2}],"updated_date":"2026-08-11T07:18:39.950985","created_date":"2025-10-10T00:00:00"}
