{"id":"https://openalex.org/W2992702773","doi":"https://doi.org/10.1109/lgrs.2019.2953892","title":"Complex-Valued Full Convolutional Neural Network for SAR Target Classification","display_name":"Complex-Valued Full Convolutional Neural Network for SAR Target Classification","publication_year":2019,"publication_date":"2019-12-03","ids":{"openalex":"https://openalex.org/W2992702773","doi":"https://doi.org/10.1109/lgrs.2019.2953892","mag":"2992702773"},"language":"en","primary_location":{"id":"doi:10.1109/lgrs.2019.2953892","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lgrs.2019.2953892","pdf_url":null,"source":{"id":"https://openalex.org/S126920919","display_name":"IEEE Geoscience and Remote Sensing Letters","issn_l":"1545-598X","issn":["1545-598X","1558-0571"],"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 Geoscience and Remote Sensing Letters","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/A5100719444","display_name":"Lingjuan Yu","orcid":"https://orcid.org/0000-0003-1118-4792"},"institutions":[{"id":"https://openalex.org/I4510145","display_name":"Jiangxi University of Science and Technology","ror":"https://ror.org/03q0t9252","country_code":"CN","type":"education","lineage":["https://openalex.org/I4510145"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lingjuan Yu","raw_affiliation_strings":["School of Information Engineering, Jiangxi University of Science and Technology, Ganzhou, China"],"raw_orcid":"https://orcid.org/0000-0003-1118-4792","affiliations":[{"raw_affiliation_string":"School of Information Engineering, Jiangxi University of Science and Technology, Ganzhou, China","institution_ids":["https://openalex.org/I4510145"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5037863568","display_name":"Yuehong Hu","orcid":null},"institutions":[{"id":"https://openalex.org/I4210119042","display_name":"Gannan Normal University","ror":"https://ror.org/02jf7e446","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210119042"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuehong Hu","raw_affiliation_strings":["School of Physics and Electronic Information, Gannan Normal University, Ganzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Physics and Electronic Information, Gannan Normal University, Ganzhou, China","institution_ids":["https://openalex.org/I4210119042"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5053760119","display_name":"Xiaochun Xie","orcid":"https://orcid.org/0000-0002-0345-9891"},"institutions":[{"id":"https://openalex.org/I4210119042","display_name":"Gannan Normal University","ror":"https://ror.org/02jf7e446","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210119042"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaochun Xie","raw_affiliation_strings":["School of Physics and Electronic Information, Gannan Normal University, Ganzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Physics and Electronic Information, Gannan Normal University, Ganzhou, China","institution_ids":["https://openalex.org/I4210119042"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5044553388","display_name":"Yun Lin","orcid":"https://orcid.org/0000-0001-6674-780X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yun Lin","raw_affiliation_strings":["School of Information Science and Technology, Northern University of Technology, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information Science and Technology, Northern University of Technology, Beijing, China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101750735","display_name":"Wen Hong","orcid":"https://orcid.org/0000-0002-8645-2264"},"institutions":[{"id":"https://openalex.org/I4210110458","display_name":"Institute of Electronics","ror":"https://ror.org/01z143507","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210110458"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wen Hong","raw_affiliation_strings":["Institute of Electronics, Chinese Academy of Science, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Electronics, Chinese Academy of Science, Beijing, China","institution_ids":["https://openalex.org/I4210110458"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":35.9769,"has_fulltext":false,"cited_by_count":55,"citation_normalized_percentile":{"value":0.99421052,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"17","issue":"10","first_page":"1752","last_page":"1756"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11038","display_name":"Advanced SAR Imaging Techniques","score":0.9998999834060669,"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":0.9998999834060669,"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":0.9987000226974487,"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":0.9984999895095825,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/softmax-function","display_name":"Softmax function","score":0.7321212887763977},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6837556958198547},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.6708611845970154},{"id":"https://openalex.org/keywords/pooling","display_name":"Pooling","score":0.654326319694519},{"id":"https://openalex.org/keywords/overfitting","display_name":"Overfitting","score":0.56803959608078},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.547997772693634},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5384706258773804},{"id":"https://openalex.org/keywords/layer","display_name":"Layer (electronics)","score":0.4975323975086212},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4839082658290863},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.46679574251174927},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.41917699575424194},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.4086189270019531},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.36187201738357544}],"concepts":[{"id":"https://openalex.org/C188441871","wikidata":"https://www.wikidata.org/wiki/Q7554146","display_name":"Softmax function","level":3,"score":0.7321212887763977},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6837556958198547},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.6708611845970154},{"id":"https://openalex.org/C70437156","wikidata":"https://www.wikidata.org/wiki/Q7228652","display_name":"Pooling","level":2,"score":0.654326319694519},{"id":"https://openalex.org/C22019652","wikidata":"https://www.wikidata.org/wiki/Q331309","display_name":"Overfitting","level":3,"score":0.56803959608078},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.547997772693634},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5384706258773804},{"id":"https://openalex.org/C2779227376","wikidata":"https://www.wikidata.org/wiki/Q6505497","display_name":"Layer (electronics)","level":2,"score":0.4975323975086212},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4839082658290863},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.46679574251174927},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.41917699575424194},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4086189270019531},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.36187201738357544},{"id":"https://openalex.org/C178790620","wikidata":"https://www.wikidata.org/wiki/Q11351","display_name":"Organic chemistry","level":1,"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/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/lgrs.2019.2953892","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lgrs.2019.2953892","pdf_url":null,"source":{"id":"https://openalex.org/S126920919","display_name":"IEEE Geoscience and Remote Sensing Letters","issn_l":"1545-598X","issn":["1545-598X","1558-0571"],"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 Geoscience and Remote Sensing Letters","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1402023559","display_name":"\u57fa\u4e8e\u5706\u8ff9SAR\u7684\u76ee\u6807\u65b9\u4f4d\u6563\u5c04\u7279\u5f81\u63d0\u53d6\u65b9\u6cd5\u7814\u7a76","funder_award_id":"61571421","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2537594169","display_name":"\u591a\u89d2\u5ea6SAR\u6210\u50cf\u7406\u8bba\u4e0e\u65b9\u6cd5","funder_award_id":"61431018","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6273718615","display_name":null,"funder_award_id":"61501210","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":29,"referenced_works":["https://openalex.org/W322998299","https://openalex.org/W592963477","https://openalex.org/W1806891645","https://openalex.org/W2097117768","https://openalex.org/W2229484904","https://openalex.org/W2290300449","https://openalex.org/W2356798126","https://openalex.org/W2366653681","https://openalex.org/W2410591237","https://openalex.org/W2559324447","https://openalex.org/W2560288685","https://openalex.org/W2588453093","https://openalex.org/W2599199509","https://openalex.org/W2754361766","https://openalex.org/W2793189836","https://openalex.org/W2896556344","https://openalex.org/W2897760800","https://openalex.org/W2962913459","https://openalex.org/W2963274778","https://openalex.org/W2963911037","https://openalex.org/W2965344373","https://openalex.org/W2983707810","https://openalex.org/W6611190527","https://openalex.org/W6638444622","https://openalex.org/W6696670905","https://openalex.org/W6706493343","https://openalex.org/W6707984791","https://openalex.org/W6738884980","https://openalex.org/W6743857607"],"related_works":["https://openalex.org/W4362597605","https://openalex.org/W1574414179","https://openalex.org/W3107204728","https://openalex.org/W4287591324","https://openalex.org/W4297676672","https://openalex.org/W3026913501","https://openalex.org/W3134502938","https://openalex.org/W4401096132","https://openalex.org/W2899027234","https://openalex.org/W2964954556"],"abstract_inverted_index":{"Complex-valued":[0],"convolutional":[1,16],"neural":[2,17],"network":[3,18],"(CV-CNN)":[4],"has":[5],"been":[6],"presented":[7,104],"in":[8,34,49,90,105],"recent":[9],"years.":[10],"In":[11],"this":[12],"letter,":[13],"CV":[14],"full":[15],"(CV-FCNN)":[19],"is":[20,55,70,85,103,119,146],"proposed":[21],"for":[22,98],"synthetic":[23],"aperture":[24],"radar":[25],"(SAR)":[26],"target":[27,69],"classification,":[28],"which":[29],"contains":[30],"only":[31],"convolution":[32,53,83,117,160],"layers":[33,48,54],"the":[35,43,52,66,73,76,81,91,95,108,125,136,152],"hidden":[36],"layer.":[37,93,161],"The":[38,131],"purpose":[39],"of":[40,68,75,101,128],"replacing":[41],"both":[42],"pooling":[44,59],"and":[45,61,144],"fully":[46],"connected":[47],"CV-CNN":[50],"with":[51,151],"to":[56,123],"avoid":[57],"complex":[58,77,109],"operation":[60],"prevent":[62],"overfitting,":[63],"respectively.":[64],"Considering":[65],"label":[67],"always":[71],"real-valued,":[72],"magnitude":[74],"vector":[78],"obtained":[79],"from":[80],"last":[82],"layer":[84,100,118],"calculated":[86],"before":[87],"softmax":[88],"classification":[89],"output":[92],"Moreover,":[94],"back-propagation":[96],"formula":[97],"each":[99],"CV-FCNN":[102,122,150],"detail.":[106],"Furthermore,":[107],"<inline-formula":[110,153],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[111,154],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">":[112,155],"<tex-math":[113,156],"notation=\"LaTeX\">$1\\times":[114,157],"1$":[115,158],"</tex-math></inline-formula>":[116,159],"added":[120],"into":[121],"learn":[124],"cross-channel":[126],"information":[127],"feature":[129],"maps.":[130],"experimental":[132],"results":[133],"show":[134],"that":[135],"average":[137],"accuracy":[138],"can":[139],"be":[140],"improved":[141,148],"using":[142,149],"CV-FCNN,":[143],"it":[145],"further":[147]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":10},{"year":2024,"cited_by_count":11},{"year":2023,"cited_by_count":13},{"year":2022,"cited_by_count":11},{"year":2021,"cited_by_count":9}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
