{"id":"https://openalex.org/W2987358755","doi":"https://doi.org/10.1109/igarss.2019.8898943","title":"Polsar Land Cover Classification via Tensorial Embedding Methods","display_name":"Polsar Land Cover Classification via Tensorial Embedding Methods","publication_year":2019,"publication_date":"2019-07-01","ids":{"openalex":"https://openalex.org/W2987358755","doi":"https://doi.org/10.1109/igarss.2019.8898943","mag":"2987358755"},"language":"en","primary_location":{"id":"doi:10.1109/igarss.2019.8898943","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2019.8898943","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium","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/A5041413561","display_name":"Bo Ren","orcid":"https://orcid.org/0000-0002-0481-5069"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Bo Ren","raw_affiliation_strings":["School of Artificial Intelligence, Xidian University, Xi\u2019an, China","School of Artificial Intelligence, Xidian University, Xi'an, China"],"affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, Xidian University, Xi\u2019an, China","institution_ids":["https://openalex.org/I149594827"]},{"raw_affiliation_string":"School of Artificial Intelligence, Xidian University, Xi'an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5043022387","display_name":"Biao Hou","orcid":"https://orcid.org/0000-0002-1996-186X"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Biao Hou","raw_affiliation_strings":["School of Artificial Intelligence, Xidian University, Xi\u2019an, China","School of Artificial Intelligence, Xidian University, Xi'an, China"],"affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, Xidian University, Xi\u2019an, China","institution_ids":["https://openalex.org/I149594827"]},{"raw_affiliation_string":"School of Artificial Intelligence, Xidian University, Xi'an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5106124934","display_name":"Jocelyn Chanussot","orcid":"https://orcid.org/0000-0003-4817-2875"},"institutions":[{"id":"https://openalex.org/I106785703","display_name":"Institut polytechnique de Grenoble","ror":"https://ror.org/05sbt2524","country_code":"FR","type":"education","lineage":["https://openalex.org/I106785703","https://openalex.org/I899635006"]},{"id":"https://openalex.org/I4210124956","display_name":"Grenoble Images Parole Signal Automatique","ror":"https://ror.org/02wrme198","country_code":"FR","type":"facility","lineage":["https://openalex.org/I106785703","https://openalex.org/I1294671590","https://openalex.org/I4210124956","https://openalex.org/I899635006","https://openalex.org/I899635006"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Jocelyn Chanussot","raw_affiliation_strings":["Signal and Images Department, Grenoble Institute of Technology, Grenoble, France"],"affiliations":[{"raw_affiliation_string":"Signal and Images Department, Grenoble Institute of Technology, Grenoble, France","institution_ids":["https://openalex.org/I4210124956","https://openalex.org/I106785703"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5040622906","display_name":"Changzhe Jiao","orcid":"https://orcid.org/0000-0002-1392-8348"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Changzhe Jiao","raw_affiliation_strings":["School of Artificial Intelligence, Xidian University, Xi\u2019an, China","School of Artificial Intelligence, Xidian University, Xi'an, China"],"affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, Xidian University, Xi\u2019an, China","institution_ids":["https://openalex.org/I149594827"]},{"raw_affiliation_string":"School of Artificial Intelligence, Xidian University, Xi'an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5049776440","display_name":"Xiangrong Zhang","orcid":"https://orcid.org/0000-0003-0379-2042"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiangrong Zhang","raw_affiliation_strings":["School of Artificial Intelligence, Xidian University, Xi\u2019an, China","School of Artificial Intelligence, Xidian University, Xi'an, China"],"affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, Xidian University, Xi\u2019an, China","institution_ids":["https://openalex.org/I149594827"]},{"raw_affiliation_string":"School of Artificial Intelligence, Xidian University, Xi'an, China","institution_ids":["https://openalex.org/I149594827"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5041413561"],"corresponding_institution_ids":["https://openalex.org/I149594827"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.07884682,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"38","issue":null,"first_page":"1224","last_page":"1227"},"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":0.9991000294685364,"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":0.9991000294685364,"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/T10689","display_name":"Remote-Sensing Image Classification","score":0.9944000244140625,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"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/T11312","display_name":"Soil Moisture and Remote Sensing","score":0.9815000295639038,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6683803200721741},{"id":"https://openalex.org/keywords/kernelization","display_name":"Kernelization","score":0.6650790572166443},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.6634238958358765},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6083189249038696},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5694886445999146},{"id":"https://openalex.org/keywords/synthetic-aperture-radar","display_name":"Synthetic aperture radar","score":0.5043071508407593},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5009050369262695},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.46754780411720276},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.43993836641311646},{"id":"https://openalex.org/keywords/feature-vector","display_name":"Feature vector","score":0.4316473603248596},{"id":"https://openalex.org/keywords/land-cover","display_name":"Land cover","score":0.41575688123703003},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.30606991052627563},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.19549912214279175},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.09521275758743286}],"concepts":[{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6683803200721741},{"id":"https://openalex.org/C207225210","wikidata":"https://www.wikidata.org/wiki/Q1759539","display_name":"Kernelization","level":3,"score":0.6650790572166443},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.6634238958358765},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6083189249038696},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5694886445999146},{"id":"https://openalex.org/C87360688","wikidata":"https://www.wikidata.org/wiki/Q740686","display_name":"Synthetic aperture radar","level":2,"score":0.5043071508407593},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5009050369262695},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.46754780411720276},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.43993836641311646},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.4316473603248596},{"id":"https://openalex.org/C2780648208","wikidata":"https://www.wikidata.org/wiki/Q3001793","display_name":"Land cover","level":3,"score":0.41575688123703003},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.30606991052627563},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.19549912214279175},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.09521275758743286},{"id":"https://openalex.org/C4792198","wikidata":"https://www.wikidata.org/wiki/Q1165944","display_name":"Land use","level":2,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0},{"id":"https://openalex.org/C147176958","wikidata":"https://www.wikidata.org/wiki/Q77590","display_name":"Civil engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/igarss.2019.8898943","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2019.8898943","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6700000166893005,"id":"https://metadata.un.org/sdg/15","display_name":"Life in Land"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":11,"referenced_works":["https://openalex.org/W1967455454","https://openalex.org/W1991111993","https://openalex.org/W2018775529","https://openalex.org/W2052190325","https://openalex.org/W2141200867","https://openalex.org/W2152993203","https://openalex.org/W2158188163","https://openalex.org/W2792151357","https://openalex.org/W2793189836","https://openalex.org/W2811368253","https://openalex.org/W3148981562"],"related_works":["https://openalex.org/W3020640542","https://openalex.org/W2292973071","https://openalex.org/W2476602023","https://openalex.org/W2381408042","https://openalex.org/W2350505296","https://openalex.org/W4210966920","https://openalex.org/W2156233651","https://openalex.org/W2550009779","https://openalex.org/W2043913960","https://openalex.org/W4390143830"],"abstract_inverted_index":{"In":[0,80],"recent":[1],"years,":[2],"graph":[3],"embedding":[4,87],"has":[5],"become":[6,71],"a":[7,26,42,72,95],"significant":[8],"technique":[9],"to":[10,54,76,89],"deal":[11],"with":[12],"feature":[13,97],"extraction":[14],"and":[15,22,32,50,60,64],"dimension":[16],"reduction":[17],"problems.":[18],"Under":[19],"the":[20,66,85,91,100,108],"linearization":[21],"kernelization,":[23],"it":[24],"provides":[25],"unified":[27],"framework":[28],"in":[29],"machine":[30],"learning":[31],"other":[33],"pattern":[34],"recognition":[35],"tasks.":[36],"Polarimetric":[37],"synthetic":[38],"aperture":[39],"(PolSAR)":[40],"as":[41],"typical":[43],"multi-channel":[44],"sensor":[45],"can":[46],"obtain":[47],"more":[48],"geometrical":[49],"geophysical":[51],"information.":[52],"How":[53],"combine":[55],"those":[56],"polarimetric":[57],"scattering":[58],"signals":[59],"target":[61],"decomposition":[62],"features":[63,93],"explore":[65],"spatial":[67],"information":[68],"between":[69],"pixels":[70],"new":[73],"research":[74],"direction":[75],"address":[77],"PolSAR":[78,101],"data.":[79],"this":[81],"paper,":[82],"we":[83],"utilize":[84],"tensorial":[86],"methods":[88,110],"extract":[90],"intrinsic":[92],"from":[94],"redundant":[96],"space":[98],"for":[99],"land":[102],"cover":[103],"classification.":[104],"The":[105],"effectiveness":[106],"of":[107],"proposed":[109],"is":[111],"demonstrated":[112],"using":[113],"AIRSAR":[114],"Flevoland":[115],"data":[116],"set.":[117]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
