{"id":"https://openalex.org/W1985250350","doi":"https://doi.org/10.1109/igarss.2015.7326486","title":"Ship detection in polarimetric SAR images via tensor robust principle component analysis","display_name":"Ship detection in polarimetric SAR images via tensor robust principle component analysis","publication_year":2015,"publication_date":"2015-07-01","ids":{"openalex":"https://openalex.org/W1985250350","doi":"https://doi.org/10.1109/igarss.2015.7326486","mag":"1985250350"},"language":"en","primary_location":{"id":"doi:10.1109/igarss.2015.7326486","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2015.7326486","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5101976384","display_name":"Shengli Song","orcid":"https://orcid.org/0000-0002-6580-6158"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shengli Song","raw_affiliation_strings":["Department of Electronic Engineering, Tsinghua University, Beijing, China","Department of Electronic Engineering, Tsinghua University, Beijing, CHINA#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electronic Engineering, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]},{"raw_affiliation_string":"Department of Electronic Engineering, Tsinghua University, Beijing, CHINA#TAB#","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5037577175","display_name":"Jian Yang","orcid":"https://orcid.org/0000-0003-4887-3444"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jian Yang","raw_affiliation_strings":["Department of Electronic Engineering, Tsinghua University, Beijing, China","Department of Electronic Engineering, Tsinghua University, Beijing, CHINA#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electronic Engineering, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]},{"raw_affiliation_string":"Department of Electronic Engineering, Tsinghua University, Beijing, CHINA#TAB#","institution_ids":["https://openalex.org/I99065089"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I99065089"],"apc_list":null,"apc_paid":null,"fwci":1.7822,"has_fulltext":false,"cited_by_count":16,"citation_normalized_percentile":{"value":0.8402263,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"3152","last_page":"3155"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10801","display_name":"Synthetic Aperture Radar (SAR) Applications and Techniques","score":0.9995999932289124,"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/T10801","display_name":"Synthetic Aperture Radar (SAR) Applications and Techniques","score":0.9995999932289124,"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/T11038","display_name":"Advanced SAR Imaging Techniques","score":0.9958000183105469,"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/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9911999702453613,"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/polarimetry","display_name":"Polarimetry","score":0.7245540618896484},{"id":"https://openalex.org/keywords/tensor","display_name":"Tensor (intrinsic definition)","score":0.6517521739006042},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6058607697486877},{"id":"https://openalex.org/keywords/robust-principal-component-analysis","display_name":"Robust principal component analysis","score":0.5738041400909424},{"id":"https://openalex.org/keywords/detector","display_name":"Detector","score":0.5624053478240967},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5359687805175781},{"id":"https://openalex.org/keywords/sliding-window-protocol","display_name":"Sliding window protocol","score":0.5185707211494446},{"id":"https://openalex.org/keywords/structure-tensor","display_name":"Structure tensor","score":0.49538886547088623},{"id":"https://openalex.org/keywords/synthetic-aperture-radar","display_name":"Synthetic aperture radar","score":0.4555450975894928},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.45277127623558044},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.4472113251686096},{"id":"https://openalex.org/keywords/component","display_name":"Component (thermodynamics)","score":0.4388730227947235},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.35710981488227844},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.29128456115722656},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.21356341242790222},{"id":"https://openalex.org/keywords/principal-component-analysis","display_name":"Principal component analysis","score":0.19119077920913696},{"id":"https://openalex.org/keywords/window","display_name":"Window (computing)","score":0.1906217634677887},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.11478045582771301},{"id":"https://openalex.org/keywords/optics","display_name":"Optics","score":0.07075434923171997}],"concepts":[{"id":"https://openalex.org/C28493345","wikidata":"https://www.wikidata.org/wiki/Q899381","display_name":"Polarimetry","level":3,"score":0.7245540618896484},{"id":"https://openalex.org/C155281189","wikidata":"https://www.wikidata.org/wiki/Q3518150","display_name":"Tensor (intrinsic definition)","level":2,"score":0.6517521739006042},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6058607697486877},{"id":"https://openalex.org/C2777749129","wikidata":"https://www.wikidata.org/wiki/Q17148469","display_name":"Robust principal component analysis","level":3,"score":0.5738041400909424},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.5624053478240967},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5359687805175781},{"id":"https://openalex.org/C102392041","wikidata":"https://www.wikidata.org/wiki/Q592860","display_name":"Sliding window protocol","level":3,"score":0.5185707211494446},{"id":"https://openalex.org/C113315163","wikidata":"https://www.wikidata.org/wiki/Q7625159","display_name":"Structure tensor","level":3,"score":0.49538886547088623},{"id":"https://openalex.org/C87360688","wikidata":"https://www.wikidata.org/wiki/Q740686","display_name":"Synthetic aperture radar","level":2,"score":0.4555450975894928},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.45277127623558044},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.4472113251686096},{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.4388730227947235},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.35710981488227844},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.29128456115722656},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.21356341242790222},{"id":"https://openalex.org/C27438332","wikidata":"https://www.wikidata.org/wiki/Q2873","display_name":"Principal component analysis","level":2,"score":0.19119077920913696},{"id":"https://openalex.org/C2778751112","wikidata":"https://www.wikidata.org/wiki/Q835016","display_name":"Window (computing)","level":2,"score":0.1906217634677887},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.11478045582771301},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.07075434923171997},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C191486275","wikidata":"https://www.wikidata.org/wiki/Q210028","display_name":"Scattering","level":2,"score":0.0},{"id":"https://openalex.org/C97355855","wikidata":"https://www.wikidata.org/wiki/Q11473","display_name":"Thermodynamics","level":1,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/igarss.2015.7326486","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2015.7326486","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":6,"referenced_works":["https://openalex.org/W1999136078","https://openalex.org/W2068746745","https://openalex.org/W2077717067","https://openalex.org/W2145962650","https://openalex.org/W2913535645","https://openalex.org/W4244393449"],"related_works":["https://openalex.org/W3196545307","https://openalex.org/W2469797871","https://openalex.org/W3198574147","https://openalex.org/W3072262295","https://openalex.org/W4206996224","https://openalex.org/W3105774572","https://openalex.org/W4308121881","https://openalex.org/W2604768956","https://openalex.org/W1985250350","https://openalex.org/W2896613709"],"abstract_inverted_index":{"In":[0],"order":[1],"to":[2,78],"avoid":[3],"the":[4,14,47,79,90,103],"disadvantages":[5],"of":[6,13,28,73],"CFAR":[7,49],"detector":[8],"and":[9,51,54],"make":[10],"full":[11],"use":[12],"polarimetric":[15,29,60,91],"information,":[16],"a":[17,67],"novel":[18],"method":[19,42,95,105],"is":[20,43,63,76,96],"proposed":[21,104],"in":[22],"this":[23],"paper":[24],"for":[25],"detecting":[26],"ships":[27],"SAR":[30,61],"images,":[31],"based":[32],"on":[33],"tensor":[34,74,80],"robust":[35],"principle":[36],"component":[37],"analysis":[38],"(tensor":[39],"RPCA).":[40],"This":[41],"completely":[44],"different":[45],"from":[46],"traditional":[48],"detector,":[50],"distribution":[52],"model":[53],"sliding":[55],"window":[56],"are":[57],"unnecessary.":[58],"The":[59],"image":[62],"firstly":[64],"depicted":[65],"by":[66,81],"tensor,":[68],"then":[69],"an":[70],"improved":[71],"version":[72],"RPCA":[75],"applied":[77],"using":[82],"accelerated":[83],"proximal":[84],"gradient":[85],"(APG)":[86],"algorithm.":[87],"For":[88],"comparison,":[89],"whitening":[92],"filter":[93],"(PWF)":[94],"also":[97],"used.":[98],"Experiment":[99],"results":[100],"show":[101],"that":[102],"has":[106],"excellent":[107],"performance.":[108]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":2},{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
