{"id":"https://openalex.org/W7147009209","doi":"https://doi.org/10.1109/cnml68938.2026.11452432","title":"Adaptive ship target recognition method based on deep learning","display_name":"Adaptive ship target recognition method based on deep learning","publication_year":2026,"publication_date":"2026-01-30","ids":{"openalex":"https://openalex.org/W7147009209","doi":"https://doi.org/10.1109/cnml68938.2026.11452432"},"language":null,"primary_location":{"id":"doi:10.1109/cnml68938.2026.11452432","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cnml68938.2026.11452432","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2026 International Conference on Communication Networks and Machine Learning (CNML)","raw_type":"proceedings-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/A5132634725","display_name":"Rongxin Liu","orcid":null},"institutions":[{"id":"https://openalex.org/I27357992","display_name":"Dalian University of Technology","ror":"https://ror.org/023hj5876","country_code":"CN","type":"education","lineage":["https://openalex.org/I27357992"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Rongxin Liu","raw_affiliation_strings":["Technology Institute,Dalian Scientific Test and Control,Dalian,China"],"affiliations":[{"raw_affiliation_string":"Technology Institute,Dalian Scientific Test and Control,Dalian,China","institution_ids":["https://openalex.org/I27357992"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100420016","display_name":"F. Richard Yu","orcid":"https://orcid.org/0000-0003-1006-7594"},"institutions":[{"id":"https://openalex.org/I27357992","display_name":"Dalian University of Technology","ror":"https://ror.org/023hj5876","country_code":"CN","type":"education","lineage":["https://openalex.org/I27357992"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fan Yu","raw_affiliation_strings":["Technology Institute,Dalian Scientific Test and Control,Dalian,China"],"affiliations":[{"raw_affiliation_string":"Technology Institute,Dalian Scientific Test and Control,Dalian,China","institution_ids":["https://openalex.org/I27357992"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5132571168","display_name":"Chuanyang Ge","orcid":null},"institutions":[{"id":"https://openalex.org/I27357992","display_name":"Dalian University of Technology","ror":"https://ror.org/023hj5876","country_code":"CN","type":"education","lineage":["https://openalex.org/I27357992"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chuanyang Ge","raw_affiliation_strings":["Technology Institute,Dalian Scientific Test and Control,Dalian,China"],"affiliations":[{"raw_affiliation_string":"Technology Institute,Dalian Scientific Test and Control,Dalian,China","institution_ids":["https://openalex.org/I27357992"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5132634725"],"corresponding_institution_ids":["https://openalex.org/I27357992"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.93493377,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"544","last_page":"549"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11698","display_name":"Underwater Acoustics Research","score":0.32659998536109924,"subfield":{"id":"https://openalex.org/subfields/1910","display_name":"Oceanography"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11698","display_name":"Underwater Acoustics Research","score":0.32659998536109924,"subfield":{"id":"https://openalex.org/subfields/1910","display_name":"Oceanography"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12131","display_name":"Wireless Signal Modulation Classification","score":0.18639999628067017,"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/T11038","display_name":"Advanced SAR Imaging Techniques","score":0.16930000483989716,"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/hilbert\u2013huang-transform","display_name":"Hilbert\u2013Huang transform","score":0.7271000146865845},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6050999760627747},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.5992000102996826},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5821999907493591},{"id":"https://openalex.org/keywords/signal","display_name":"SIGNAL (programming language)","score":0.5654000043869019},{"id":"https://openalex.org/keywords/envelope","display_name":"Envelope (radar)","score":0.5077999830245972},{"id":"https://openalex.org/keywords/smoothing","display_name":"Smoothing","score":0.48410001397132874},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.44749999046325684},{"id":"https://openalex.org/keywords/underwater","display_name":"Underwater","score":0.4050999879837036},{"id":"https://openalex.org/keywords/time\u2013frequency-analysis","display_name":"Time\u2013frequency analysis","score":0.4004000127315521}],"concepts":[{"id":"https://openalex.org/C25570617","wikidata":"https://www.wikidata.org/wiki/Q1006462","display_name":"Hilbert\u2013Huang transform","level":3,"score":0.7271000146865845},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.699999988079071},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6050999760627747},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.5992000102996826},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5821999907493591},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.5654000043869019},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5482000112533569},{"id":"https://openalex.org/C65155139","wikidata":"https://www.wikidata.org/wiki/Q5380912","display_name":"Envelope (radar)","level":3,"score":0.5077999830245972},{"id":"https://openalex.org/C3770464","wikidata":"https://www.wikidata.org/wiki/Q775963","display_name":"Smoothing","level":2,"score":0.48410001397132874},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.44749999046325684},{"id":"https://openalex.org/C98083399","wikidata":"https://www.wikidata.org/wiki/Q3246517","display_name":"Underwater","level":2,"score":0.4050999879837036},{"id":"https://openalex.org/C142433447","wikidata":"https://www.wikidata.org/wiki/Q7806653","display_name":"Time\u2013frequency analysis","level":3,"score":0.4004000127315521},{"id":"https://openalex.org/C45273575","wikidata":"https://www.wikidata.org/wiki/Q578970","display_name":"Spectrogram","level":2,"score":0.399399995803833},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.38609999418258667},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3781000077724457},{"id":"https://openalex.org/C11930861","wikidata":"https://www.wikidata.org/wiki/Q181417","display_name":"Frequency modulation","level":3,"score":0.3668000102043152},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.3659999966621399},{"id":"https://openalex.org/C29265498","wikidata":"https://www.wikidata.org/wiki/Q7047719","display_name":"Noise measurement","level":3,"score":0.35409998893737793},{"id":"https://openalex.org/C137798554","wikidata":"https://www.wikidata.org/wiki/Q6038852","display_name":"Instantaneous phase","level":3,"score":0.3424000144004822},{"id":"https://openalex.org/C67467970","wikidata":"https://www.wikidata.org/wiki/Q1292425","display_name":"Underwater acoustics","level":3,"score":0.3343999981880188},{"id":"https://openalex.org/C117623542","wikidata":"https://www.wikidata.org/wiki/Q621974","display_name":"Automatic target recognition","level":3,"score":0.3303999900817871},{"id":"https://openalex.org/C100675267","wikidata":"https://www.wikidata.org/wiki/Q1371624","display_name":"Background noise","level":2,"score":0.3140999972820282},{"id":"https://openalex.org/C104267543","wikidata":"https://www.wikidata.org/wiki/Q208163","display_name":"Signal processing","level":3,"score":0.3125999867916107},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.30250000953674316},{"id":"https://openalex.org/C123079801","wikidata":"https://www.wikidata.org/wiki/Q750240","display_name":"Modulation (music)","level":2,"score":0.3021000027656555},{"id":"https://openalex.org/C33676613","wikidata":"https://www.wikidata.org/wiki/Q13415176","display_name":"Dimension (graph theory)","level":2,"score":0.2978000044822693},{"id":"https://openalex.org/C2778775528","wikidata":"https://www.wikidata.org/wiki/Q5135432","display_name":"Closing (real estate)","level":2,"score":0.2955000102519989},{"id":"https://openalex.org/C13944312","wikidata":"https://www.wikidata.org/wiki/Q7512748","display_name":"Signal-to-noise ratio (imaging)","level":2,"score":0.29190000891685486},{"id":"https://openalex.org/C48677424","wikidata":"https://www.wikidata.org/wiki/Q6888088","display_name":"Mode (computer interface)","level":2,"score":0.28690001368522644},{"id":"https://openalex.org/C102248274","wikidata":"https://www.wikidata.org/wiki/Q168388","display_name":"Adaptive filter","level":2,"score":0.28029999136924744},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.2639999985694885},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.2581999897956848},{"id":"https://openalex.org/C24890656","wikidata":"https://www.wikidata.org/wiki/Q82811","display_name":"Acoustics","level":1,"score":0.25600001215934753},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.2540000081062317}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cnml68938.2026.11452432","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cnml68938.2026.11452432","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2026 International Conference on Communication Networks and Machine Learning (CNML)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/14","score":0.7616158723831177,"display_name":"Life below water"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":7,"referenced_works":["https://openalex.org/W2000982976","https://openalex.org/W2086068421","https://openalex.org/W3004159173","https://openalex.org/W4226262535","https://openalex.org/W4306670515","https://openalex.org/W4391735947","https://openalex.org/W4407520633"],"related_works":[],"abstract_inverted_index":{"Ship":[0],"target":[1,49,125,165],"recognition":[2,28],"is":[3,29,93,110,132,148,162],"one":[4],"of":[5,19,36,83,104,123],"the":[6,34,72,97,116,124,173,180],"key":[7],"contents":[8],"in":[9,33],"underwater":[10,37],"acoustics":[11],"research.":[12],"and":[13,26,48,119,137,167],"how":[14],"to":[15,69,90,113,134],"make":[16],"full":[17],"use":[18],"ship":[20],"radiated":[21],"noise":[22,126],"for":[23,164],"feature":[24,46],"extraction":[25,47],"classification":[27,50,166,184],"an":[30,44],"important":[31],"topic":[32],"field":[35],"acoustic":[38],"signal":[39,73,89,109,147],"processing.":[40],"This":[41,56],"paper":[42],"proposes":[43],"adaptive":[45],"method":[51,57,175],"based":[52],"on":[53,179],"deep":[54],"learning.":[55],"employs":[58],"Improved":[59],"Complete":[60],"Ensemble":[61],"Empirical":[62],"Mode":[63,85],"Decomposition":[64],"with":[65],"Adaptive":[66],"Noise":[67],"(ICEEMDAN)":[68],"adaptively":[70],"decompose":[71],"into":[74],"components":[75,100,139],"across":[76],"different":[77],"frequency":[78],"bands,":[79],"yielding":[80],"various":[81],"orders":[82],"Intrinsic":[84],"Functions":[86],"(IMFs).":[87],"The":[88,107,144],"be":[91],"demodulated":[92],"reconstructed":[94,108,145],"by":[95],"summing":[96],"strongly":[98],"modulated":[99],"through":[101],"a":[102,158],"judgment":[103],"envelope":[105],"entropy.":[106],"then":[111],"analyzed":[112,149],"obtain":[114],"both":[115],"continuous":[117],"spectrum":[118,121],"line":[120],"features":[122],"modulation":[127],"spectrum.":[128],"Concurrently,":[129],"each":[130],"IMF":[131],"subjected":[133],"smoothing":[135],"filtering,":[136],"all":[138],"are":[140],"subsequently":[141],"summed":[142],"again.":[143],"denoised":[146],"using":[150],"Low":[151],"Frequency":[152],"Analysis":[153],"Recording":[154],"(LOFAR)":[155],"spectrograms.":[156],"Finally,":[157],"multi-feature":[159],"fusion":[160],"model":[161],"utilized":[163],"recognition.":[168],"Experimental":[169],"results":[170],"indicate":[171],"that":[172],"proposed":[174],"demonstrates":[176],"robust":[177],"performance":[178],"dataset,":[181],"exhibiting":[182],"favorable":[183],"effectiveness.":[185]},"counts_by_year":[],"updated_date":"2026-04-02T13:53:19.096889","created_date":"2026-04-02T00:00:00"}
