{"id":"https://openalex.org/W2997085028","doi":"https://doi.org/10.1109/tgrs.2019.2957453","title":"LDGAN: A Synthetic Aperture Radar Image Generation Method for Automatic Target Recognition","display_name":"LDGAN: A Synthetic Aperture Radar Image Generation Method for Automatic Target Recognition","publication_year":2019,"publication_date":"2019-12-24","ids":{"openalex":"https://openalex.org/W2997085028","doi":"https://doi.org/10.1109/tgrs.2019.2957453","mag":"2997085028"},"language":"en","primary_location":{"id":"doi:10.1109/tgrs.2019.2957453","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2019.2957453","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/A5073006428","display_name":"Changjie Cao","orcid":null},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Changjie Cao","raw_affiliation_strings":["School of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu, China"],"raw_orcid":"https://orcid.org/0000-0003-3579-9636","affiliations":[{"raw_affiliation_string":"School of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu, China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5019411747","display_name":"Zongjie Cao","orcid":"https://orcid.org/0000-0002-0117-9087"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zongjie Cao","raw_affiliation_strings":["Center for Information Geoscience, UESTC, Chengdu, China","School of Information and Communication Engineering, University of Electronic Science and Technology of China (UESTC), Chengdu, China"],"raw_orcid":"https://orcid.org/0000-0002-0117-9087","affiliations":[{"raw_affiliation_string":"Center for Information Geoscience, UESTC, Chengdu, China","institution_ids":["https://openalex.org/I150229711"]},{"raw_affiliation_string":"School of Information and Communication Engineering, University of Electronic Science and Technology of China (UESTC), Chengdu, China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5061245960","display_name":"Zongyong Cui","orcid":"https://orcid.org/0000-0003-1155-786X"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zongyong Cui","raw_affiliation_strings":["School of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu, China"],"raw_orcid":"https://orcid.org/0000-0003-1155-786X","affiliations":[{"raw_affiliation_string":"School of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu, China","institution_ids":["https://openalex.org/I150229711"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I150229711"],"apc_list":null,"apc_paid":null,"fwci":39.5746,"has_fulltext":false,"cited_by_count":77,"citation_normalized_percentile":{"value":0.99500308,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":100},"biblio":{"volume":"58","issue":"5","first_page":"3495","last_page":"3508"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11038","display_name":"Advanced SAR Imaging Techniques","score":0.9997000098228455,"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":0.9997000098228455,"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/T11609","display_name":"Geophysical Methods and Applications","score":0.9958999752998352,"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/T10801","display_name":"Synthetic Aperture Radar (SAR) Applications and Techniques","score":0.9919000267982483,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8140213489532471},{"id":"https://openalex.org/keywords/automatic-target-recognition","display_name":"Automatic target recognition","score":0.8015507459640503},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7556324005126953},{"id":"https://openalex.org/keywords/synthetic-aperture-radar","display_name":"Synthetic aperture radar","score":0.6913227438926697},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5793015956878662},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.55784010887146},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.4376786947250366},{"id":"https://openalex.org/keywords/independence","display_name":"Independence (probability theory)","score":0.43486180901527405},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4251294732093811},{"id":"https://openalex.org/keywords/function","display_name":"Function (biology)","score":0.4222424328327179},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.4147574305534363},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.10904017090797424}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8140213489532471},{"id":"https://openalex.org/C117623542","wikidata":"https://www.wikidata.org/wiki/Q621974","display_name":"Automatic target recognition","level":3,"score":0.8015507459640503},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7556324005126953},{"id":"https://openalex.org/C87360688","wikidata":"https://www.wikidata.org/wiki/Q740686","display_name":"Synthetic aperture radar","level":2,"score":0.6913227438926697},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5793015956878662},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.55784010887146},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.4376786947250366},{"id":"https://openalex.org/C35651441","wikidata":"https://www.wikidata.org/wiki/Q625303","display_name":"Independence (probability theory)","level":2,"score":0.43486180901527405},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4251294732093811},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.4222424328327179},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.4147574305534363},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.10904017090797424},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C78458016","wikidata":"https://www.wikidata.org/wiki/Q840400","display_name":"Evolutionary biology","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tgrs.2019.2957453","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2019.2957453","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":[],"awards":[{"id":"https://openalex.org/G6684014802","display_name":null,"funder_award_id":"61801098","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6814906260","display_name":null,"funder_award_id":"2672018ZYGX2018J013","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":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":42,"referenced_works":["https://openalex.org/W1557094547","https://openalex.org/W2033753253","https://openalex.org/W2038591350","https://openalex.org/W2099471712","https://openalex.org/W2102544846","https://openalex.org/W2105628133","https://openalex.org/W2111703458","https://openalex.org/W2111758425","https://openalex.org/W2124648367","https://openalex.org/W2125389028","https://openalex.org/W2132012856","https://openalex.org/W2137772040","https://openalex.org/W2138287042","https://openalex.org/W2148791593","https://openalex.org/W2269648248","https://openalex.org/W2396308676","https://openalex.org/W2410591237","https://openalex.org/W2559324447","https://openalex.org/W2587706859","https://openalex.org/W2588453093","https://openalex.org/W2607666785","https://openalex.org/W2614504311","https://openalex.org/W2730249686","https://openalex.org/W2737047298","https://openalex.org/W2739748921","https://openalex.org/W2772879006","https://openalex.org/W2786355301","https://openalex.org/W2806263990","https://openalex.org/W2900755281","https://openalex.org/W2962879692","https://openalex.org/W2963226019","https://openalex.org/W2963684088","https://openalex.org/W2964201867","https://openalex.org/W4295521014","https://openalex.org/W4320013936","https://openalex.org/W6633571969","https://openalex.org/W6678815747","https://openalex.org/W6685352114","https://openalex.org/W6718140377","https://openalex.org/W6732249622","https://openalex.org/W6735913928","https://openalex.org/W6741832134"],"related_works":["https://openalex.org/W3137365474","https://openalex.org/W2886347302","https://openalex.org/W2784759481","https://openalex.org/W1545594509","https://openalex.org/W3130755980","https://openalex.org/W3038591045","https://openalex.org/W1988723959","https://openalex.org/W2540650467","https://openalex.org/W2773828237","https://openalex.org/W2521772843"],"abstract_inverted_index":{"Under":[0],"the":[1,18,72,76,81,86,95,106,110,124,132,136,140,143,147,158,176,202,205,211,215,221,228,232,235,239,253,264,269,277],"framework":[2],"of":[3,20,85,109,118,182,185,195,223,234,243],"a":[4,29,39,115,248],"supervised":[5],"learning-based":[6],"automatic":[7],"target":[8,120],"recognition":[9,12,61],"(ATR)":[10],"approach,":[11],"performance":[13,233],"is":[14,28,102,149,281],"primarily":[15],"dependent":[16],"on":[17,169],"amount":[19],"training":[21,26,278],"samples.":[22],"However,":[23],"shortage":[24],"in":[25,152,188,238],"samples":[27,56],"consistent":[30],"issue":[31,159],"for":[32,60,71,256,274],"ATR.":[33,240,257],"In":[34],"this":[35,153],"article,":[36],"we":[37],"propose":[38],"new":[40,68,137],"image":[41,43,237,255],"to":[42,57,79,105,112,131,155,166,251,271],"generation":[44,174],"method,":[45],"called":[46],"label-directed":[47],"generative":[48,88],"adversarial":[49,89],"networks":[50,90],"(LDGANs),":[51],"which":[52,74],"will":[53],"provide":[54],"labeled":[55],"be":[58],"used":[59],"model":[62],"training.":[63],"We":[64],"define":[65],"an":[66],"entirely":[67],"loss":[69,107],"function":[70,108],"LDGAN,":[73],"utilizes":[75],"Wasserstein":[77],"distance":[78,83],"replace":[80],"original":[82],"measurement":[84],"conventional":[87],"(GANs),":[91],"thus":[92],"efficiently":[93],"avoiding":[94],"collapse":[96],"mode":[97],"problem.":[98],"The":[99,258],"label":[100],"information":[101,273,280],"also":[103,127,150,230,261],"added":[104],"LDGAN":[111,148,216],"avoid":[113],"generating":[114],"large":[116],"number":[117],"unlabeled":[119],"images.":[121],"More":[122],"importantly,":[123],"proposed":[125,265],"method":[126,266],"makes":[128],"corresponding":[129],"changes":[130],"network":[133],"architecture":[134],"regarding":[135],"GANs.":[138],"At":[139],"same":[141],"time,":[142],"detailed":[144],"algorithm":[145],"about":[146],"introduced":[151],"article":[154],"deal":[156],"with":[157,171],"that":[160,210,263],"characteristically":[161],"GANs":[162],"are":[163],"not":[164],"easy":[165],"train.":[167],"Based":[168],"comparisons":[170],"other":[172],"directed":[173],"methods,":[175],"experimental":[177,245,259],"results":[178,181,219,246,260],"show":[179],"comparative":[180],"several":[183],"types":[184],"generated":[186,213,236,254],"images":[187,212],"statistical":[189],"features,":[190,192],"gradient":[191],"classic":[193],"features":[194],"synthetic":[196],"aperture":[197],"radar":[198],"(SAR)":[199],"targets":[200],"and":[201,225],"independence":[203],"from":[204],"real":[206],"image.":[207],"While":[208],"demonstrating":[209],"by":[214],"produced":[217],"better":[218,249],"using":[220],"assumptions":[222],"independent":[224],"identical":[226],"distribution,":[227],"experiment":[229],"explores":[231],"A":[241],"comparison":[242],"these":[244],"demonstrates":[247],"way":[250],"use":[252],"prove":[262],"does":[267],"have":[268],"ability":[270],"supplement":[272],"ATR":[275],"when":[276],"sample":[279],"insufficient.":[282]},"counts_by_year":[{"year":2026,"cited_by_count":9},{"year":2025,"cited_by_count":9},{"year":2024,"cited_by_count":21},{"year":2023,"cited_by_count":16},{"year":2022,"cited_by_count":11},{"year":2021,"cited_by_count":10},{"year":2020,"cited_by_count":1}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}