{"id":"https://openalex.org/W2916576002","doi":"https://doi.org/10.1587/transinf.2018edl8158","title":"Millimeter-Wave InSAR Target Recognition with Deep Convolutional Neural Network","display_name":"Millimeter-Wave InSAR Target Recognition with Deep Convolutional Neural Network","publication_year":2019,"publication_date":"2019-02-28","ids":{"openalex":"https://openalex.org/W2916576002","doi":"https://doi.org/10.1587/transinf.2018edl8158","mag":"2916576002"},"language":"en","primary_location":{"id":"doi:10.1587/transinf.2018edl8158","is_oa":true,"landing_page_url":"https://doi.org/10.1587/transinf.2018edl8158","pdf_url":"https://www.jstage.jst.go.jp/article/transinf/E102.D/3/E102.D_2018EDL8158/_pdf","source":{"id":"https://openalex.org/S2486202937","display_name":"IEICE Transactions on Information and Systems","issn_l":"0916-8532","issn":["0916-8532","1745-1361"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4320800604","host_organization_name":"Institute of Electronics, Information and Communication Engineers","host_organization_lineage":["https://openalex.org/P4320800604"],"host_organization_lineage_names":["Institute of Electronics, Information and Communication Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEICE Transactions on Information and Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://www.jstage.jst.go.jp/article/transinf/E102.D/3/E102.D_2018EDL8158/_pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5058321483","display_name":"Yilu Ma","orcid":null},"institutions":[{"id":"https://openalex.org/I36399199","display_name":"Nanjing University of Science and Technology","ror":"https://ror.org/00xp9wg62","country_code":"CN","type":"education","lineage":["https://openalex.org/I36399199"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yilu MA","raw_affiliation_strings":["School of Electronic and Optical Engineering, Nanjing University of Science and Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electronic and Optical Engineering, Nanjing University of Science and Technology","institution_ids":["https://openalex.org/I36399199"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100721626","display_name":"Yuehua Li","orcid":"https://orcid.org/0000-0002-3838-958X"},"institutions":[{"id":"https://openalex.org/I36399199","display_name":"Nanjing University of Science and Technology","ror":"https://ror.org/00xp9wg62","country_code":"CN","type":"education","lineage":["https://openalex.org/I36399199"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuehua LI","raw_affiliation_strings":["School of Electronic and Optical Engineering, Nanjing University of Science and Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electronic and Optical Engineering, Nanjing University of Science and Technology","institution_ids":["https://openalex.org/I36399199"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I36399199"],"apc_list":null,"apc_paid":null,"fwci":7.1954,"has_fulltext":true,"cited_by_count":5,"citation_normalized_percentile":{"value":0.96835227,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"E102.D","issue":"3","first_page":"655","last_page":"658"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11038","display_name":"Advanced SAR Imaging Techniques","score":0.9998999834060669,"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":0.9998999834060669,"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/T11609","display_name":"Geophysical Methods and Applications","score":0.9983000159263611,"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"}},{"id":"https://openalex.org/T10801","display_name":"Synthetic Aperture Radar (SAR) Applications and Techniques","score":0.998199999332428,"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/computer-science","display_name":"Computer science","score":0.7849639654159546},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7674945592880249},{"id":"https://openalex.org/keywords/interferometric-synthetic-aperture-radar","display_name":"Interferometric synthetic aperture radar","score":0.6907778978347778},{"id":"https://openalex.org/keywords/extremely-high-frequency","display_name":"Extremely high frequency","score":0.5295815467834473},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4268919825553894},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3689664304256439},{"id":"https://openalex.org/keywords/synthetic-aperture-radar","display_name":"Synthetic aperture radar","score":0.1766504943370819},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.15715163946151733}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7849639654159546},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7674945592880249},{"id":"https://openalex.org/C22286887","wikidata":"https://www.wikidata.org/wiki/Q1666056","display_name":"Interferometric synthetic aperture radar","level":3,"score":0.6907778978347778},{"id":"https://openalex.org/C45764600","wikidata":"https://www.wikidata.org/wiki/Q570342","display_name":"Extremely high frequency","level":2,"score":0.5295815467834473},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4268919825553894},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3689664304256439},{"id":"https://openalex.org/C87360688","wikidata":"https://www.wikidata.org/wiki/Q740686","display_name":"Synthetic aperture radar","level":2,"score":0.1766504943370819},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.15715163946151733}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1587/transinf.2018edl8158","is_oa":true,"landing_page_url":"https://doi.org/10.1587/transinf.2018edl8158","pdf_url":"https://www.jstage.jst.go.jp/article/transinf/E102.D/3/E102.D_2018EDL8158/_pdf","source":{"id":"https://openalex.org/S2486202937","display_name":"IEICE Transactions on Information and Systems","issn_l":"0916-8532","issn":["0916-8532","1745-1361"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4320800604","host_organization_name":"Institute of Electronics, Information and Communication Engineers","host_organization_lineage":["https://openalex.org/P4320800604"],"host_organization_lineage_names":["Institute of Electronics, Information and Communication Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEICE Transactions on Information and Systems","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1587/transinf.2018edl8158","is_oa":true,"landing_page_url":"https://doi.org/10.1587/transinf.2018edl8158","pdf_url":"https://www.jstage.jst.go.jp/article/transinf/E102.D/3/E102.D_2018EDL8158/_pdf","source":{"id":"https://openalex.org/S2486202937","display_name":"IEICE Transactions on Information and Systems","issn_l":"0916-8532","issn":["0916-8532","1745-1361"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4320800604","host_organization_name":"Institute of Electronics, Information and Communication Engineers","host_organization_lineage":["https://openalex.org/P4320800604"],"host_organization_lineage_names":["Institute of Electronics, Information and Communication Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEICE Transactions on Information and Systems","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2916576002.pdf","grobid_xml":"https://content.openalex.org/works/W2916576002.grobid-xml"},"referenced_works_count":8,"referenced_works":["https://openalex.org/W1529984115","https://openalex.org/W2015861736","https://openalex.org/W2110609587","https://openalex.org/W2126738384","https://openalex.org/W2410591237","https://openalex.org/W2584820752","https://openalex.org/W2611467245","https://openalex.org/W2770553941"],"related_works":["https://openalex.org/W2373310320","https://openalex.org/W2781934594","https://openalex.org/W4384163768","https://openalex.org/W2790032735","https://openalex.org/W4385499758","https://openalex.org/W2387499565","https://openalex.org/W4382365962","https://openalex.org/W2767118615","https://openalex.org/W2033914206","https://openalex.org/W2042327336"],"abstract_inverted_index":{"Target":[0],"recognition":[1,18,80,114,182],"in":[2,29],"Millimeter-wave":[3],"Interferometric":[4],"Synthetic":[5],"Aperture":[6],"Radiometer":[7],"(MMW":[8],"InSAR)":[9],"imaging":[10,37,154],"is":[11],"always":[12],"a":[13,65,116],"crucial":[14],"task.":[15,183],"However,":[16],"the":[17,86,91,93,97,102,105,112,123,128,138,143,160,168,181],"performance":[19,179],"of":[20,39,83,104],"conventional":[21],"algorithms":[22],"degrades":[23],"when":[24],"facing":[25],"unpredictable":[26],"noise":[27],"interference":[28],"practical":[30],"scenarios":[31],"and":[32,52,71,110,175],"information-loss":[33,150],"caused":[34],"by":[35,149,152],"inverse":[36,153],"processing":[38],"InSAR.":[40],"These":[41],"difficulties":[42],"make":[43],"it":[44],"very":[45],"necessary":[46],"to":[47,90,173],"develop":[48],"general-purpose":[49],"denoising":[50,66,108],"techniques":[51],"robust":[53,124],"feature":[54,125],"extractors":[55],"for":[56],"InSAR":[57,77,88,140,163],"target":[58,79,113],"recognition.":[59],"In":[60],"this":[61],"paper,":[62],"we":[63],"propose":[64],"convolutional":[67],"neural":[68],"network":[69],"(D-CNN)":[70],"demonstrate":[72],"its":[73],"advantage":[74],"on":[75,137,159,180],"MMW":[76,87,139,162],"automatic":[78],"problem.":[81],"Instead":[82],"directly":[84],"feeding":[85],"image":[89],"CNN,":[92],"proposed":[94],"algorithm":[95],"utilizes":[96],"visibility":[98],"function":[99],"samples":[100],"as":[101,115],"input":[103],"fully":[106],"connected":[107],"layer":[109],"recasts":[111],"data-driven":[117],"supervised":[118],"learning":[119],"task,":[120],"which":[121,135],"learns":[122],"representations":[126],"from":[127],"space-frequency":[129],"domain.":[130],"Comparing":[131],"with":[132],"traditional":[133],"methods":[134],"act":[136],"output":[141],"images,":[142],"D-CNN":[144,169],"will":[145],"not":[146],"be":[147],"affected":[148],"accused":[151],"process.":[155],"Furthermore,":[156],"experimental":[157],"results":[158],"simulated":[161],"images":[164],"dataset":[165],"illustrate":[166],"that":[167],"has":[170],"superior":[171],"immunity":[172],"noise,":[174],"achieves":[176],"an":[177],"outstanding":[178]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}