{"id":"https://openalex.org/W3209666651","doi":"https://doi.org/10.1145/3479162.3479186","title":"A Small-sample Radar Target Classification Method Based on DCGAN-SE-ResNeXt","display_name":"A Small-sample Radar Target Classification Method Based on DCGAN-SE-ResNeXt","publication_year":2021,"publication_date":"2021-07-16","ids":{"openalex":"https://openalex.org/W3209666651","doi":"https://doi.org/10.1145/3479162.3479186","mag":"3209666651"},"language":"en","primary_location":{"id":"doi:10.1145/3479162.3479186","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3479162.3479186","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 9th International Conference on Computer and Communications Management","raw_type":"proceedings-article"},"type":"conference-paper","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/A5012421248","display_name":"Wenhan Meng","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wenhan Meng","raw_affiliation_strings":["Early Warning Academy, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Early Warning Academy, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5077528633","display_name":"Qiang Lin","orcid":"https://orcid.org/0000-0002-3842-2634"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Qiang Lin","raw_affiliation_strings":["Early Warning Academy, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Early Warning Academy, China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100444208","display_name":"Yichi Zhang","orcid":"https://orcid.org/0009-0009-3001-7384"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yichi Zhang","raw_affiliation_strings":["Early Warning Academy, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Early Warning Academy, China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"156","last_page":"165"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11038","display_name":"Advanced SAR Imaging Techniques","score":0.9976999759674072,"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":0.9976999759674072,"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/T14158","display_name":"Optical Systems and Laser Technology","score":0.9933000206947327,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic 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/T12153","display_name":"Advanced Optical Sensing Technologies","score":0.9868999719619751,"subfield":{"id":"https://openalex.org/subfields/3105","display_name":"Instrumentation"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/radar","display_name":"Radar","score":0.8336108922958374},{"id":"https://openalex.org/keywords/sample","display_name":"Sample (material)","score":0.5634725093841553},{"id":"https://openalex.org/keywords/sequence","display_name":"Sequence (biology)","score":0.5578659772872925},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5395160913467407},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5313559174537659},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.47891151905059814},{"id":"https://openalex.org/keywords/range","display_name":"Range (aeronautics)","score":0.47594285011291504},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4588099718093872},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4513194262981415},{"id":"https://openalex.org/keywords/radar-imaging","display_name":"Radar imaging","score":0.44794440269470215},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.41658154129981995},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2683089077472687},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.19866880774497986},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.07463154196739197},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.06091684103012085}],"concepts":[{"id":"https://openalex.org/C554190296","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar","level":2,"score":0.8336108922958374},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.5634725093841553},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.5578659772872925},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5395160913467407},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5313559174537659},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.47891151905059814},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.47594285011291504},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4588099718093872},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4513194262981415},{"id":"https://openalex.org/C10929652","wikidata":"https://www.wikidata.org/wiki/Q7279985","display_name":"Radar imaging","level":3,"score":0.44794440269470215},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.41658154129981995},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2683089077472687},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.19866880774497986},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.07463154196739197},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.06091684103012085},{"id":"https://openalex.org/C97355855","wikidata":"https://www.wikidata.org/wiki/Q11473","display_name":"Thermodynamics","level":1,"score":0.0},{"id":"https://openalex.org/C146978453","wikidata":"https://www.wikidata.org/wiki/Q3798668","display_name":"Aerospace engineering","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/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","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/C54355233","wikidata":"https://www.wikidata.org/wiki/Q7162","display_name":"Genetics","level":1,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3479162.3479186","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3479162.3479186","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 9th International Conference on Computer and Communications Management","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W2064076387","https://openalex.org/W2161304138","https://openalex.org/W2194775991","https://openalex.org/W2392320334","https://openalex.org/W2549139847","https://openalex.org/W2752782242","https://openalex.org/W2985650004","https://openalex.org/W2999923950","https://openalex.org/W3113292629","https://openalex.org/W3132793057","https://openalex.org/W3168082197","https://openalex.org/W3171357516","https://openalex.org/W3177525997","https://openalex.org/W4206628288","https://openalex.org/W6645729211"],"related_works":["https://openalex.org/W3147584709","https://openalex.org/W2977677679","https://openalex.org/W1992327129","https://openalex.org/W2381986121","https://openalex.org/W2370918718","https://openalex.org/W2112284452","https://openalex.org/W2256933480","https://openalex.org/W4313855562","https://openalex.org/W2053819089","https://openalex.org/W2091422131"],"abstract_inverted_index":{"Small-sample":[0],"radar":[1,12,37,66,90,120,157],"target":[2,40,67,101],"classification":[3,24,68,112,138,149],"has":[4],"always":[5],"been":[6],"a":[7,19],"difficult":[8],"problem":[9],"in":[10,63],"the":[11,43,55,85,93,114,129,134,148,152],"reference":[13],"field.":[14],"To":[15],"solve":[16],"this":[17],"problem,":[18],"set":[20],"of":[21,36,49,54,59,89,113,119,125,133,144,151,156],"comprehensive":[22],"solution":[23],"method":[25],"combining":[26],"DCGAN":[27,81],"and":[28,70,92,111,127],"SE-ResNeXt":[29,104],"is":[30,140],"proposed,":[31],"aiming":[32],"at":[33],"overcoming":[34],"ac-curacy":[35],"small":[38],"sample":[39],"classification.":[41],"At":[42],"same":[44],"time,":[45],"through":[46],"multiple":[47],"sets":[48],"comparative":[50],"experiments,":[51],"in-depth":[52],"analysis":[53],"model":[56],"performance":[57],"changes":[58],"different":[60],"learning":[61],"algorithms":[62],"actual":[64],"small-sample":[65],"scene,":[69],"two":[71],"important":[72],"conclusions":[73],"that":[74,143],"can":[75,82,96,105],"effectively":[76,83,106],"guide":[77],"engineering":[78],"applications:":[79],"First,":[80],"expand":[84],"sequence":[86,116,153],"range":[87,117,154],"profile":[88,118,155],"echo,":[91,121],"expanded":[94],"samples":[95],"be":[97],"used":[98],"for":[99,147],"subsequent":[100],"classification;":[102],"Second,":[103],"carry":[107],"out":[108],"feature":[109],"extraction":[110],"extended":[115],"with":[122],"an":[123],"accuracy":[124,139],"95.63%,":[126],"test":[128],"optimal":[130],"expansion":[131],"coefficient":[132],"current":[135],"sample.":[136],"The":[137],"better":[141],"than":[142],"other":[145],"methods":[146],"effect":[150],"echo.":[158]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}