{"id":"https://openalex.org/W3049367857","doi":"https://doi.org/10.1109/tkde.2020.3016208","title":"Tensor Canonical Correlation Analysis Networks for Multi-View Remote Sensing Scene Recognition","display_name":"Tensor Canonical Correlation Analysis Networks for Multi-View Remote Sensing Scene Recognition","publication_year":2020,"publication_date":"2020-08-14","ids":{"openalex":"https://openalex.org/W3049367857","doi":"https://doi.org/10.1109/tkde.2020.3016208","mag":"3049367857"},"language":"en","primary_location":{"id":"doi:10.1109/tkde.2020.3016208","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tkde.2020.3016208","pdf_url":null,"source":{"id":"https://openalex.org/S30698027","display_name":"IEEE Transactions on Knowledge and Data Engineering","issn_l":"1041-4347","issn":["1041-4347","1558-2191","2326-3865"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Knowledge and Data Engineering","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://opus.lib.uts.edu.au/bitstream/10453/145749/2/Binder1.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5034521535","display_name":"Xinghao Yang","orcid":"https://orcid.org/0000-0001-6487-3183"},"institutions":[{"id":"https://openalex.org/I114017466","display_name":"University of Technology Sydney","ror":"https://ror.org/03f0f6041","country_code":"AU","type":"education","lineage":["https://openalex.org/I114017466"]}],"countries":["AU"],"is_corresponding":true,"raw_author_name":"Xinghao Yang","raw_affiliation_strings":["Faculty of Engineering and Information Technology, School of Computer Science, University of Technology Sydney, Ultimo, NSW, Australia"],"affiliations":[{"raw_affiliation_string":"Faculty of Engineering and Information Technology, School of Computer Science, University of Technology Sydney, Ultimo, NSW, Australia","institution_ids":["https://openalex.org/I114017466"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100444156","display_name":"Weifeng Liu","orcid":"https://orcid.org/0000-0002-5388-9080"},"institutions":[{"id":"https://openalex.org/I114017466","display_name":"University of Technology Sydney","ror":"https://ror.org/03f0f6041","country_code":"AU","type":"education","lineage":["https://openalex.org/I114017466"]},{"id":"https://openalex.org/I4210162190","display_name":"China University of Petroleum, East China","ror":"https://ror.org/05gbn2817","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210162190"]}],"countries":["AU","CN"],"is_corresponding":false,"raw_author_name":"Weifeng Liu","raw_affiliation_strings":["Faculty of Engineering and Information Technology, School of Computer Science, University of Technology Sydney, Ultimo, NSW, Australia","School of Information and Control Engineering, China University of Petroleum (East China), Qingdao, China"],"affiliations":[{"raw_affiliation_string":"Faculty of Engineering and Information Technology, School of Computer Science, University of Technology Sydney, Ultimo, NSW, Australia","institution_ids":["https://openalex.org/I114017466"]},{"raw_affiliation_string":"School of Information and Control Engineering, China University of Petroleum (East China), Qingdao, China","institution_ids":["https://openalex.org/I4210162190"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100431652","display_name":"Wei Liu","orcid":"https://orcid.org/0000-0001-6565-5815"},"institutions":[{"id":"https://openalex.org/I114017466","display_name":"University of Technology Sydney","ror":"https://ror.org/03f0f6041","country_code":"AU","type":"education","lineage":["https://openalex.org/I114017466"]},{"id":"https://openalex.org/I4210162190","display_name":"China University of Petroleum, East China","ror":"https://ror.org/05gbn2817","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210162190"]}],"countries":["AU","CN"],"is_corresponding":false,"raw_author_name":"Wei Liu","raw_affiliation_strings":["Faculty of Engineering and Information Technology, School of Computer Science, University of Technology Sydney, Ultimo, NSW, Australia","School of Information and Control Engineering, China University of Petroleum (East China), Qingdao, China"],"affiliations":[{"raw_affiliation_string":"Faculty of Engineering and Information Technology, School of Computer Science, University of Technology Sydney, Ultimo, NSW, Australia","institution_ids":["https://openalex.org/I114017466"]},{"raw_affiliation_string":"School of Information and Control Engineering, China University of Petroleum (East China), Qingdao, China","institution_ids":["https://openalex.org/I4210162190"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5034521535"],"corresponding_institution_ids":["https://openalex.org/I114017466"],"apc_list":null,"apc_paid":null,"fwci":2.1021,"has_fulltext":true,"cited_by_count":23,"citation_normalized_percentile":{"value":0.89959424,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"34","issue":"6","first_page":"2948","last_page":"2961"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9969000220298767,"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"}},"topics":[{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9969000220298767,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9889000058174133,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"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":0.9832000136375427,"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":0.7424548864364624},{"id":"https://openalex.org/keywords/canonical-correlation","display_name":"Canonical correlation","score":0.7379604578018188},{"id":"https://openalex.org/keywords/covariance","display_name":"Covariance","score":0.6433942317962646},{"id":"https://openalex.org/keywords/tensor","display_name":"Tensor (intrinsic definition)","score":0.6379855275154114},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6206310391426086},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5808088183403015},{"id":"https://openalex.org/keywords/principal-component-analysis","display_name":"Principal component analysis","score":0.5722053050994873},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.548736572265625},{"id":"https://openalex.org/keywords/multiset","display_name":"Multiset","score":0.5085681676864624},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4784988462924957},{"id":"https://openalex.org/keywords/histogram","display_name":"Histogram","score":0.4574354290962219},{"id":"https://openalex.org/keywords/correlation","display_name":"Correlation","score":0.4561549723148346},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.4436587989330292},{"id":"https://openalex.org/keywords/covariance-matrix","display_name":"Covariance matrix","score":0.4411361813545227},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.258769690990448},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1938014030456543},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.12886255979537964}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7424548864364624},{"id":"https://openalex.org/C153874254","wikidata":"https://www.wikidata.org/wiki/Q115542","display_name":"Canonical correlation","level":2,"score":0.7379604578018188},{"id":"https://openalex.org/C178650346","wikidata":"https://www.wikidata.org/wiki/Q201984","display_name":"Covariance","level":2,"score":0.6433942317962646},{"id":"https://openalex.org/C155281189","wikidata":"https://www.wikidata.org/wiki/Q3518150","display_name":"Tensor (intrinsic definition)","level":2,"score":0.6379855275154114},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6206310391426086},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5808088183403015},{"id":"https://openalex.org/C27438332","wikidata":"https://www.wikidata.org/wiki/Q2873","display_name":"Principal component analysis","level":2,"score":0.5722053050994873},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.548736572265625},{"id":"https://openalex.org/C2779623528","wikidata":"https://www.wikidata.org/wiki/Q864377","display_name":"Multiset","level":2,"score":0.5085681676864624},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4784988462924957},{"id":"https://openalex.org/C53533937","wikidata":"https://www.wikidata.org/wiki/Q185020","display_name":"Histogram","level":3,"score":0.4574354290962219},{"id":"https://openalex.org/C117220453","wikidata":"https://www.wikidata.org/wiki/Q5172842","display_name":"Correlation","level":2,"score":0.4561549723148346},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.4436587989330292},{"id":"https://openalex.org/C185142706","wikidata":"https://www.wikidata.org/wiki/Q1134404","display_name":"Covariance matrix","level":2,"score":0.4411361813545227},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.258769690990448},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1938014030456543},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.12886255979537964},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","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},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tkde.2020.3016208","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tkde.2020.3016208","pdf_url":null,"source":{"id":"https://openalex.org/S30698027","display_name":"IEEE Transactions on Knowledge and Data Engineering","issn_l":"1041-4347","issn":["1041-4347","1558-2191","2326-3865"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Knowledge and Data Engineering","raw_type":"journal-article"},{"id":"pmh:oai:opus.lib.uts.edu.au:10453/145749","is_oa":true,"landing_page_url":"http://hdl.handle.net/10453/145749","pdf_url":"https://opus.lib.uts.edu.au/bitstream/10453/145749/2/Binder1.pdf","source":{"id":"https://openalex.org/S4306401357","display_name":"UTS ePRESS (University of Technology Sydney)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I114017466","host_organization_name":"University of Technology Sydney","host_organization_lineage":["https://openalex.org/I114017466"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Journal Article"}],"best_oa_location":{"id":"pmh:oai:opus.lib.uts.edu.au:10453/145749","is_oa":true,"landing_page_url":"http://hdl.handle.net/10453/145749","pdf_url":"https://opus.lib.uts.edu.au/bitstream/10453/145749/2/Binder1.pdf","source":{"id":"https://openalex.org/S4306401357","display_name":"UTS ePRESS (University of Technology Sydney)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I114017466","host_organization_name":"University of Technology Sydney","host_organization_lineage":["https://openalex.org/I114017466"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Journal Article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G4838037128","display_name":null,"funder_award_id":"202000009","funder_id":"https://openalex.org/F4320326873","funder_display_name":"National Laboratory of Pattern Recognition"}],"funders":[{"id":"https://openalex.org/F4320326873","display_name":"National Laboratory of Pattern Recognition","ror":null}],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W3049367857.pdf"},"referenced_works_count":67,"referenced_works":["https://openalex.org/W258213556","https://openalex.org/W1522301498","https://openalex.org/W1616262590","https://openalex.org/W1670132599","https://openalex.org/W1672347394","https://openalex.org/W1686810756","https://openalex.org/W1865067283","https://openalex.org/W1917395817","https://openalex.org/W1958291604","https://openalex.org/W1977904037","https://openalex.org/W1980349018","https://openalex.org/W1997893060","https://openalex.org/W2000215628","https://openalex.org/W2013081398","https://openalex.org/W2015386604","https://openalex.org/W2018282388","https://openalex.org/W2019092234","https://openalex.org/W2024106491","https://openalex.org/W2025603201","https://openalex.org/W2049677900","https://openalex.org/W2072072671","https://openalex.org/W2090424610","https://openalex.org/W2121238376","https://openalex.org/W2131846894","https://openalex.org/W2145072179","https://openalex.org/W2152057649","https://openalex.org/W2155893237","https://openalex.org/W2163808566","https://openalex.org/W2165731615","https://openalex.org/W2194775991","https://openalex.org/W2211843587","https://openalex.org/W2253590344","https://openalex.org/W2312858779","https://openalex.org/W2321627895","https://openalex.org/W2341545927","https://openalex.org/W2342880667","https://openalex.org/W2347115704","https://openalex.org/W2412588858","https://openalex.org/W2466055095","https://openalex.org/W2524999024","https://openalex.org/W2570903723","https://openalex.org/W2744582969","https://openalex.org/W2751112250","https://openalex.org/W2752782242","https://openalex.org/W2765739551","https://openalex.org/W2766954643","https://openalex.org/W2782068553","https://openalex.org/W2887785636","https://openalex.org/W2890732922","https://openalex.org/W2897819140","https://openalex.org/W2914427239","https://openalex.org/W2919115771","https://openalex.org/W2948329096","https://openalex.org/W2955280751","https://openalex.org/W2955671895","https://openalex.org/W2963542991","https://openalex.org/W3102431071","https://openalex.org/W4241451204","https://openalex.org/W4246193833","https://openalex.org/W4298082496","https://openalex.org/W6629368666","https://openalex.org/W6631190155","https://openalex.org/W6636883489","https://openalex.org/W6637373629","https://openalex.org/W6657814759","https://openalex.org/W6684191040","https://openalex.org/W6704443453"],"related_works":["https://openalex.org/W1984946761","https://openalex.org/W2157498938","https://openalex.org/W2131436045","https://openalex.org/W2762769322","https://openalex.org/W2578144857","https://openalex.org/W1508127764","https://openalex.org/W2320012436","https://openalex.org/W2533762355","https://openalex.org/W1545779705","https://openalex.org/W2792134523"],"abstract_inverted_index":{"Convolutional":[0],"neural":[1],"network":[2,33,38,130],"(CNN)":[3],"has":[4],"been":[5,27],"proven":[6],"an":[7],"effective":[8],"way":[9],"to":[10,80,132,171,188],"extract":[11,189],"high-level":[12],"features":[13],"from":[14,68],"remote":[15],"sensing":[16],"(RS)":[17],"images":[18],"automatically.":[19],"Many":[20],"variants":[21],"of":[22,96,146,184,192,213],"the":[23,62,89,103,125,152,161,173,193,211],"CNN":[24],"model":[25],"have":[26],"proposed,":[28],"including":[29],"principal":[30],"component":[31],"analysis":[32,37,129],"(PCANet),":[34],"canonical":[35,127],"correlation":[36,91,128],"(CCANet),":[39],"multiple":[40],"scale":[41],"CCANet":[42,46],"(MS-CCANet)":[43],"and":[44,75,113,150,167,207,215],"multiview":[45],"(MCCANet).":[47],"The":[48],"PCANet":[49],"is":[50],"specialized":[51],"for":[52,217],"single":[53],"view":[54,84],"feature":[55],"abstraction,":[56],"while":[57],"in":[58],"many":[59,69],"real-world":[60],"practices,":[61],"RS":[63,194,218],"data":[64,195],"are":[65],"frequently":[66],"observed":[67],"more":[70,83],"views.":[71],"Although":[72],"CCANet,":[73],"MS-CCANet":[74],"MCCANet":[76],"can":[77,107],"be":[78,109],"applied":[79],"two":[81],"or":[82],"data,":[85],"they":[86],"consider":[87],"only":[88,108],"pair-wise":[90],"by":[92,111,141,155,196],"calculating":[93],"a":[94,157,180],"series":[95],"<italic":[97],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[98],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">two-order</i>":[99],"covariance":[100,158],"matrices.":[101],"However,":[102],"high-order":[104],"consistence,":[105],"which":[106],"explored":[110],"collectively":[112],"simultaneously":[114,142],"examining":[115],"all":[116,198],"views,":[117],"remains":[118],"undiscovered.":[119],"In":[120],"this":[121,134],"paper,":[122],"we":[123,164,177],"propose":[124],"tensor":[126],"(TCCANet)":[131],"tackle":[133],"problem.":[135],"Particularly,":[136],"TCCANet":[137,214],"learns":[138],"filter":[139],"banks":[140],"maximizing":[143],"arbitrary":[144],"number":[145],"views":[147],"with":[148],"high-order-correlation":[149],"solves":[151],"optimization":[153],"problem":[154],"decomposing":[156],"tensor.":[159],"After":[160],"convolutional":[162,200],"stage,":[163],"utilize":[165],"binarization":[166],"block-wise":[168],"histogram":[169],"strategies":[170],"generate":[172],"final":[174],"feature.":[175],"Furthermore,":[176],"also":[178],"develop":[179],"Multiple":[181],"Scale":[182],"version":[183],"TCCANet,":[185],"i.e.,":[186],"MS-TCCANet,":[187],"enriched":[190],"representation":[191],"incorporating":[197],"previous":[199],"layers.":[201],"Numerical":[202],"experiment":[203],"results":[204],"on":[205],"RSSCN7":[206],"SAT-6":[208],"datasets":[209],"demonstrate":[210],"advantages":[212],"MS-TCCANet":[216],"scene":[219],"recognition.":[220]},"counts_by_year":[{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":1}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}
