{"id":"https://openalex.org/W7147706190","doi":"https://doi.org/10.1109/cnml68938.2026.11453288","title":"Passive Sonar Target Recognition Based on Dual-Branch Feature Extraction and Adaptive Time-Frequency Fusion","display_name":"Passive Sonar Target Recognition Based on Dual-Branch Feature Extraction and Adaptive Time-Frequency Fusion","publication_year":2026,"publication_date":"2026-01-30","ids":{"openalex":"https://openalex.org/W7147706190","doi":"https://doi.org/10.1109/cnml68938.2026.11453288"},"language":null,"primary_location":{"id":"doi:10.1109/cnml68938.2026.11453288","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cnml68938.2026.11453288","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/A5132565118","display_name":"Shuyi Shen","orcid":null},"institutions":[{"id":"https://openalex.org/I4210144142","display_name":"Hangzhou Institute of Applied Acoustics","ror":"https://ror.org/0473ary24","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210144142"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Shuyi Shen","raw_affiliation_strings":["Hangzhou Applied Acoustics Research Institute,Science and Technology on Sonar Laboratory,Hangzhou,China"],"affiliations":[{"raw_affiliation_string":"Hangzhou Applied Acoustics Research Institute,Science and Technology on Sonar Laboratory,Hangzhou,China","institution_ids":["https://openalex.org/I4210144142"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5132565118"],"corresponding_institution_ids":["https://openalex.org/I4210144142"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.95,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"482","last_page":"487"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11698","display_name":"Underwater Acoustics Research","score":0.5116999745368958,"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":0.5116999745368958,"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/T11038","display_name":"Advanced SAR Imaging Techniques","score":0.4002000093460083,"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/T11192","display_name":"Underwater Vehicles and Communication Systems","score":0.01860000006854534,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.8149999976158142},{"id":"https://openalex.org/keywords/sonar","display_name":"Sonar","score":0.7455999851226807},{"id":"https://openalex.org/keywords/fusion","display_name":"Fusion","score":0.66839998960495},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.6118999719619751},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5694000124931335},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5067999958992004},{"id":"https://openalex.org/keywords/sensor-fusion","display_name":"Sensor fusion","score":0.4932999908924103},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.4016999900341034}],"concepts":[{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.8149999976158142},{"id":"https://openalex.org/C555745239","wikidata":"https://www.wikidata.org/wiki/Q133220","display_name":"Sonar","level":2,"score":0.7455999851226807},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7204999923706055},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.66839998960495},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.6118999719619751},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5976999998092651},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5694000124931335},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5067999958992004},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.4932999908924103},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4634999930858612},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.4016999900341034},{"id":"https://openalex.org/C117623542","wikidata":"https://www.wikidata.org/wiki/Q621974","display_name":"Automatic target recognition","level":3,"score":0.38580000400543213},{"id":"https://openalex.org/C69744172","wikidata":"https://www.wikidata.org/wiki/Q860822","display_name":"Image fusion","level":3,"score":0.34860000014305115},{"id":"https://openalex.org/C2988494973","wikidata":"https://www.wikidata.org/wiki/Q179448","display_name":"Noise immunity","level":3,"score":0.3427000045776367},{"id":"https://openalex.org/C137184094","wikidata":"https://www.wikidata.org/wiki/Q6764300","display_name":"Marine mammals and sonar","level":3,"score":0.3287000060081482},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.3151000142097473},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.28119999170303345},{"id":"https://openalex.org/C142433447","wikidata":"https://www.wikidata.org/wiki/Q7806653","display_name":"Time\u2013frequency analysis","level":3,"score":0.27959999442100525},{"id":"https://openalex.org/C70710897","wikidata":"https://www.wikidata.org/wiki/Q680081","display_name":"Separable space","level":2,"score":0.2662999927997589},{"id":"https://openalex.org/C2779726219","wikidata":"https://www.wikidata.org/wiki/Q7685884","display_name":"Target acquisition","level":2,"score":0.257999986410141}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cnml68938.2026.11453288","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cnml68938.2026.11453288","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","display_name":"Life below water","score":0.8536990880966187}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W1582774210","https://openalex.org/W2466903746","https://openalex.org/W3172124183","https://openalex.org/W4309459219","https://openalex.org/W4319970148","https://openalex.org/W4386028620","https://openalex.org/W4391938812","https://openalex.org/W4392092925","https://openalex.org/W4392370280","https://openalex.org/W4393352675","https://openalex.org/W4393642631","https://openalex.org/W4401691864","https://openalex.org/W7118825183"],"related_works":[],"abstract_inverted_index":{"To":[0],"address":[1],"the":[2,52,71,82,123],"issues":[3],"of":[4,77,108,132],"low":[5],"accuracy":[6,96],"and":[7,47,84,99,111,126,134],"poor":[8],"robustness":[9,113],"in":[10],"passive":[11,143],"sonar":[12,144],"target":[13,145],"recognition":[14],"under":[15],"complex":[16],"marine":[17],"environments,":[18],"this":[19],"paper":[20,103],"proposes":[21],"a":[22,33,48,66,106],"time-frequency":[23,78],"cross-domain":[24],"attention":[25,68],"fusion":[26,69,131],"neural":[27],"network":[28],"(TFCA-Net).":[29],"This":[30,102],"model":[31,72],"adopts":[32],"dual-input,":[34],"dual-branch":[35],"architecture.":[36],"The":[37,115],"timedomain":[38],"branch":[39,54],"extracts":[40,56],"temporal":[41],"features":[42,58],"based":[43],"on":[44,81],"stacked":[45],"BiLSTM":[46],"self-attention":[49],"mechanism,":[50],"while":[51],"frequency-domain":[53],"efficiently":[55],"spectral":[57],"through":[59,129],"depthwise":[60],"separable":[61],"convolutions.":[62],"And":[63],"combined":[64],"with":[65,94],"crossdomain":[67],"module,":[70],"achieves":[73],"adaptive":[74],"depth":[75],"interaction":[76],"features.":[79],"Experiments":[80],"ShipsEar":[83],"DeepShip":[85],"public":[86],"datasets":[87],"demonstrate":[88],"that":[89,119],"TFCA-Net":[90,120],"outperforms":[91],"single-input":[92],"models,":[93],"maximum":[95],"reaching":[97],"98.3%":[98],"97.6%,":[100],"respectively.":[101],"also":[104],"conducts":[105],"series":[107],"ablation":[109],"experiments":[110],"noise":[112],"tests.":[114],"research":[116],"results":[117],"show":[118],"effectively":[121],"improves":[122],"accuracy,":[124],"stability,":[125],"anti-interference":[127],"capability":[128],"complementary":[130],"time":[133],"frequency":[135],"features,":[136],"providing":[137],"an":[138],"efficient":[139],"technical":[140],"solution":[141],"for":[142],"recognition.":[146]},"counts_by_year":[],"updated_date":"2026-04-02T13:53:19.096889","created_date":"2026-04-02T00:00:00"}