{"id":"https://openalex.org/W4395030853","doi":"https://doi.org/10.1145/3638884.3638944","title":"Research on UAV Target Clustering Based on Deep Manifold Mapping","display_name":"Research on UAV Target Clustering Based on Deep Manifold Mapping","publication_year":2023,"publication_date":"2023-12-14","ids":{"openalex":"https://openalex.org/W4395030853","doi":"https://doi.org/10.1145/3638884.3638944"},"language":"en","primary_location":{"id":"doi:10.1145/3638884.3638944","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3638884.3638944","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3638884.3638944","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2023 9th International Conference on Communication and Information Processing","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3638884.3638944","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5016003619","display_name":"Xuejian Feng","orcid":"https://orcid.org/0000-0002-9486-8067"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Feng Xuejian","raw_affiliation_strings":["National Key Laboratory of Scattering and Radiation, China"],"raw_orcid":"https://orcid.org/0000-0002-9486-8067","affiliations":[{"raw_affiliation_string":"National Key Laboratory of Scattering and Radiation, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5095842733","display_name":"Hao jinchuan","orcid":"https://orcid.org/0009-0005-5024-3566"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hao jinchuan","raw_affiliation_strings":["National Key Laboratory of Scattering and Radiation, China"],"raw_orcid":"https://orcid.org/0009-0005-5024-3566","affiliations":[{"raw_affiliation_string":"National Key Laboratory of Scattering and Radiation, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5029651439","display_name":"Wang Jian","orcid":"https://orcid.org/0009-0009-2591-1592"},"institutions":[{"id":"https://openalex.org/I4210156353","display_name":"58.com (China)","ror":"https://ror.org/05v15sz79","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210156353"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wang Jian","raw_affiliation_strings":["Unit 93792, China"],"raw_orcid":"https://orcid.org/0009-0009-2591-1592","affiliations":[{"raw_affiliation_string":"Unit 93792, China","institution_ids":["https://openalex.org/I4210156353"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5095842734","display_name":"Yanjin Zhang","orcid":"https://orcid.org/0009-0007-5776-7551"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang Yanjin","raw_affiliation_strings":["National Key Laboratory of Scattering and Radiation, China"],"raw_orcid":"https://orcid.org/0009-0007-5776-7551","affiliations":[{"raw_affiliation_string":"National Key Laboratory of Scattering and Radiation, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5000474413","display_name":"Chaoying Huo","orcid":"https://orcid.org/0009-0007-2308-6555"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Huo Chaoying","raw_affiliation_strings":["National Key Laboratory of Scattering and Radiation, China"],"raw_orcid":"https://orcid.org/0009-0007-2308-6555","affiliations":[{"raw_affiliation_string":"National Key Laboratory of Scattering and Radiation, China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101875246","display_name":"Hongcheng Yin","orcid":"https://orcid.org/0000-0003-3699-0643"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yin Hongcheng","raw_affiliation_strings":["National Key Laboratory of Scattering and Radiation, China"],"raw_orcid":"https://orcid.org/0000-0003-3699-0643","affiliations":[{"raw_affiliation_string":"National Key Laboratory of Scattering and Radiation, China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.38704177,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"387","last_page":"392"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.9983999729156494,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.9983999729156494,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.9973000288009644,"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/T12389","display_name":"Infrared Target Detection Methodologies","score":0.9968000054359436,"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/cluster-analysis","display_name":"Cluster analysis","score":0.8926107287406921},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7172827124595642},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6385617256164551},{"id":"https://openalex.org/keywords/dimensionality-reduction","display_name":"Dimensionality reduction","score":0.605746865272522},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5225731134414673},{"id":"https://openalex.org/keywords/nonlinear-dimensionality-reduction","display_name":"Nonlinear dimensionality reduction","score":0.45706334710121155},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.42796769738197327},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4132065773010254}],"concepts":[{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.8926107287406921},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7172827124595642},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6385617256164551},{"id":"https://openalex.org/C70518039","wikidata":"https://www.wikidata.org/wiki/Q16000077","display_name":"Dimensionality reduction","level":2,"score":0.605746865272522},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5225731134414673},{"id":"https://openalex.org/C151876577","wikidata":"https://www.wikidata.org/wiki/Q7049464","display_name":"Nonlinear dimensionality reduction","level":3,"score":0.45706334710121155},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.42796769738197327},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4132065773010254},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3638884.3638944","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3638884.3638944","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3638884.3638944","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2023 9th International Conference on Communication and Information Processing","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3638884.3638944","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3638884.3638944","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3638884.3638944","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2023 9th International Conference on Communication and Information Processing","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4395030853.pdf","grobid_xml":"https://content.openalex.org/works/W4395030853.grobid-xml"},"referenced_works_count":8,"referenced_works":["https://openalex.org/W1967847861","https://openalex.org/W2025768430","https://openalex.org/W2031081233","https://openalex.org/W2058839679","https://openalex.org/W2480364715","https://openalex.org/W2909390529","https://openalex.org/W2990593259","https://openalex.org/W3102689913"],"related_works":["https://openalex.org/W2375574759","https://openalex.org/W2383239174","https://openalex.org/W3088634662","https://openalex.org/W117517268","https://openalex.org/W3162910294","https://openalex.org/W2539700568","https://openalex.org/W2931531042","https://openalex.org/W1489327846","https://openalex.org/W4287375746","https://openalex.org/W3124275785"],"abstract_inverted_index":{"The":[0,123],"widespread":[1],"application":[2],"of":[3,13,25,51,62,89,100,129,138,151],"unmanned":[4],"aerial":[5],"vehicles":[6],"(UAVs)":[7],"has":[8],"significantly":[9],"emphasized":[10],"the":[11,22,55,66,84,98,107,114,120,127,130,135],"importance":[12],"UAV":[14,26,32,52,63,139,152],"early":[15],"warning":[16],"and":[17,118],"detection.":[18],"In":[19],"response":[20],"to":[21,46,71,77,95,112],"clustering":[23,34,50,108,121,136,149],"problem":[24],"targets,":[27,140],"this":[28],"study":[29],"proposes":[30],"a":[31,79,144],"target":[33],"method":[35,132],"that":[36],"combines":[37],"sparse":[38],"auto":[39],"encoder":[40],"(SAE)":[41],"networks":[42,76],"with":[43],"manifold":[44,93,115],"mapping":[45,94,116],"achieve":[47],"highly":[48],"accurate":[49],"targets.":[53,153],"Firstly,":[54],"one-dimensional":[56],"high":[57],"resolution":[58],"range":[59],"profiles":[60],"(HRRPs)":[61],"targets":[64],"in":[65,103,133],"trianing":[67],"dataset":[68],"are":[69,110],"subjected":[70],"feature":[72,148],"learning":[73],"through":[74],"SAE":[75],"obtain":[78,119],"well-trained":[80],"network":[81],"architecture.":[82],"Subsequently,":[83],"deep":[85],"dimensionality":[86],"reduction":[87],"features":[88,117],"test":[90],"set":[91],"undergo":[92],"further":[96],"enhance":[97],"separability":[99],"dense":[101],"data":[102],"spatial":[104],"dimension.":[105],"Finally,":[106],"algorithms":[109],"used":[111],"cluster":[113],"results.":[122],"simulation":[124],"results":[125],"demonstrate":[126],"effectiveness":[128],"proposed":[131],"improving":[134],"accuracy":[137],"which":[141],"can":[142],"provide":[143],"valuable":[145],"reference":[146],"for":[147],"analysis":[150]},"counts_by_year":[],"updated_date":"2026-07-31T08:31:51.225901","created_date":"2025-10-10T00:00:00"}
