{"id":"https://openalex.org/W4400908990","doi":"https://doi.org/10.1109/siu61531.2024.10601023","title":"Classification of Fighter Jets with Radar HRRP Data and Machine/Deep Learning Methods","display_name":"Classification of Fighter Jets with Radar HRRP Data and Machine/Deep Learning Methods","publication_year":2024,"publication_date":"2024-05-15","ids":{"openalex":"https://openalex.org/W4400908990","doi":"https://doi.org/10.1109/siu61531.2024.10601023"},"language":"en","primary_location":{"id":"doi:10.1109/siu61531.2024.10601023","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/siu61531.2024.10601023","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 32nd Signal Processing and Communications Applications Conference (SIU)","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/A5015633664","display_name":"Sedat T\u00fcre","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Sedat T\u00fcre","raw_affiliation_strings":["İstanbul Teknik Üniversitesi,Lisansüstü Eğitim Enstitüsü,İstanbul,Türkiye,34469"],"affiliations":[{"raw_affiliation_string":"İstanbul Teknik Üniversitesi,Lisansüstü Eğitim Enstitüsü,İstanbul,Türkiye,34469","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5007648588","display_name":"Sel\u00e7uk Paker","orcid":"https://orcid.org/0000-0002-1769-1835"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sel\u00e7uk Paker","raw_affiliation_strings":["İstanbul Teknik Üniversitesi,Lisansüstü Eğitim Enstitüsü,İstanbul,Türkiye,34469"],"affiliations":[{"raw_affiliation_string":"İstanbul Teknik Üniversitesi,Lisansüstü Eğitim Enstitüsü,İstanbul,Türkiye,34469","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5015633664"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.17029531,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"4"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12125","display_name":"Aerospace and Aviation Technology","score":0.9952999949455261,"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/T12125","display_name":"Aerospace and Aviation Technology","score":0.9952999949455261,"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/T11008","display_name":"Aerodynamics and Acoustics in Jet Flows","score":0.9945999979972839,"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/T10173","display_name":"Computational Fluid Dynamics and Aerodynamics","score":0.9927999973297119,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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/radar","display_name":"Radar","score":0.6796935796737671},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6176662445068359},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5981867909431458},{"id":"https://openalex.org/keywords/radar-imaging","display_name":"Radar imaging","score":0.5145913362503052},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.49157533049583435},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.32993125915527344},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.11706164479255676}],"concepts":[{"id":"https://openalex.org/C554190296","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar","level":2,"score":0.6796935796737671},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6176662445068359},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5981867909431458},{"id":"https://openalex.org/C10929652","wikidata":"https://www.wikidata.org/wiki/Q7279985","display_name":"Radar imaging","level":3,"score":0.5145913362503052},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.49157533049583435},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.32993125915527344},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.11706164479255676}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/siu61531.2024.10601023","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/siu61531.2024.10601023","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 32nd Signal Processing and Communications Applications Conference (SIU)","raw_type":"proceedings-article"},{"id":"pmh:oai:polen.itu.edu.tr:11527/69317","is_oa":false,"landing_page_url":"https://hdl.handle.net/11527/69317","pdf_url":null,"source":{"id":"https://openalex.org/S4306400460","display_name":"Istanbul Technical University Academic Open Archive (Istanbul Technical University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I48912391","host_organization_name":"Istanbul Technical University","host_organization_lineage":["https://openalex.org/I48912391"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W2731899572","https://openalex.org/W3215138031","https://openalex.org/W2058170566","https://openalex.org/W2755342338","https://openalex.org/W2772917594","https://openalex.org/W2775347418","https://openalex.org/W2166024367","https://openalex.org/W3009238340","https://openalex.org/W3116076068","https://openalex.org/W2229312674"],"abstract_inverted_index":{"The":[0,150,164],"classification":[1,74,84,123,136,151,165],"of":[2,105],"air":[3,8],"targets":[4],"is":[5,65],"crucial":[6],"in":[7],"traffic":[9],"control,":[10],"border":[11],"security,":[12],"platform":[13],"defense,":[14],"and":[15,44,55,89,114,146,161,174],"tactical":[16],"picture":[17],"compilation.":[18],"In":[19,48],"addition":[20,49],"to":[21,50,53,68],"using":[22,86,127,141,155],"radar-derived":[23],"target":[24],"dynamic":[25],"information":[26,39,59],"among":[27],"other":[28],"sensors,":[29],"high-resolution":[30],"range":[31],"profiles":[32],"(HRRP)":[33],"can":[34],"provide":[35],"significantly":[36],"more":[37],"comprehensive":[38],"about":[40],"the":[41,58,70,102,162,168],"target\u2019s":[42],"shape":[43],"dimensions":[45],"for":[46,73,132,167],"classification.":[47],"being":[51],"able":[52],"efficiently":[54],"swiftly":[56],"interpret":[57],"acquired":[60],"by":[61],"radar":[62],"systems,":[63],"it":[64],"also":[66],"necessary":[67],"generate":[69],"data":[71],"required":[72],"via":[75],"measurement":[76],"or":[77],"digital":[78],"simulation.":[79],"This":[80],"study":[81],"compares":[82],"fighters":[83,171],"performance":[85],"machine":[87,133,147],"learning":[88,91,121,148],"deep":[90,120],"on":[92,101],"HRRP":[93],"data.":[94],"For":[95],"this":[96],"goal,":[97],"many":[98],"backbones":[99],"based":[100],"basic":[103],"infrastructure":[104],"convolutional":[106],"neural":[107],"networks":[108],"(CNN)":[109],"were":[110,125,138,153,172],"investigated,":[111],"including":[112],"Alexnet":[113],"Resnet50.":[115],"Following":[116],"feature":[117,143],"extraction":[118,144],"utilizing":[119],"approaches,":[122],"results":[124,152,166],"shared":[126],"support":[128],"vector":[129],"machines":[130],"(SVM)":[131],"learning.":[134],"Furthermore,":[135],"investigations":[137],"carried":[139],"out":[140],"various":[142],"approaches":[145],"techniques.":[149],"evaluated":[154],"metrics":[156],"such":[157],"as":[158],"precision,":[159],"recall,":[160],"F1-score.":[163],"selected":[169],"sample":[170],"calculated":[173],"shared.":[175]},"counts_by_year":[],"updated_date":"2026-03-06T13:50:29.536080","created_date":"2025-10-10T00:00:00"}