{"id":"https://openalex.org/W3041614910","doi":"https://doi.org/10.1109/tgrs.2020.3004911","title":"Multiscale CNN With Autoencoder Regularization Joint Contextual Attention Network for SAR Image Classification","display_name":"Multiscale CNN With Autoencoder Regularization Joint Contextual Attention Network for SAR Image Classification","publication_year":2020,"publication_date":"2020-07-07","ids":{"openalex":"https://openalex.org/W3041614910","doi":"https://doi.org/10.1109/tgrs.2020.3004911","mag":"3041614910"},"language":"en","primary_location":{"id":"doi:10.1109/tgrs.2020.3004911","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2020.3004911","pdf_url":null,"source":{"id":"https://openalex.org/S111326731","display_name":"IEEE Transactions on Geoscience and Remote Sensing","issn_l":"0196-2892","issn":["0196-2892","1558-0644"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["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 Geoscience and Remote Sensing","raw_type":"journal-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/A5041938484","display_name":"Zitong Wu","orcid":"https://orcid.org/0000-0002-0449-9465"},"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":"Zitong Wu","raw_affiliation_strings":["Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education of China, Xidian University, Xi\u2019an, China"],"raw_orcid":"https://orcid.org/0000-0002-0449-9465","affiliations":[{"raw_affiliation_string":"Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education of China, Xidian University, Xi\u2019an, 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":["Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education of China, Xidian University, Xi\u2019an, China"],"raw_orcid":"https://orcid.org/0000-0002-1996-186X","affiliations":[{"raw_affiliation_string":"Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education of China, Xidian University, Xi\u2019an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5050630882","display_name":"Licheng Jiao","orcid":"https://orcid.org/0000-0003-3354-9617"},"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":"Licheng Jiao","raw_affiliation_strings":["School of Electronic Engineering, Xidian University, Xi\u2019an, China"],"raw_orcid":"https://orcid.org/0000-0003-3354-9617","affiliations":[{"raw_affiliation_string":"School of Electronic Engineering, Xidian University, Xi\u2019an, China","institution_ids":["https://openalex.org/I149594827"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":35.8934,"has_fulltext":false,"cited_by_count":34,"citation_normalized_percentile":{"value":0.99390492,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":99},"biblio":{"volume":"59","issue":"2","first_page":"1200","last_page":"1213"},"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/T10801","display_name":"Synthetic Aperture Radar (SAR) Applications and Techniques","score":0.9997000098228455,"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":0.9988999962806702,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.9153493642807007},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7343356013298035},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6811371445655823},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6340924501419067},{"id":"https://openalex.org/keywords/synthetic-aperture-radar","display_name":"Synthetic aperture radar","score":0.6196668148040771},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5906002521514893},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.5902029275894165},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5573371648788452},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.5019445419311523},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.4483385384082794},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.21171030402183533}],"concepts":[{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.9153493642807007},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7343356013298035},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6811371445655823},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6340924501419067},{"id":"https://openalex.org/C87360688","wikidata":"https://www.wikidata.org/wiki/Q740686","display_name":"Synthetic aperture radar","level":2,"score":0.6196668148040771},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5906002521514893},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.5902029275894165},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5573371648788452},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.5019445419311523},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.4483385384082794},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.21171030402183533},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tgrs.2020.3004911","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2020.3004911","pdf_url":null,"source":{"id":"https://openalex.org/S111326731","display_name":"IEEE Transactions on Geoscience and Remote Sensing","issn_l":"0196-2892","issn":["0196-2892","1558-0644"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["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 Geoscience and Remote Sensing","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2095133317","display_name":null,"funder_award_id":"61671350","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G359258897","display_name":null,"funder_award_id":"61621005","funder_id":"https://openalex.org/F4320327720","funder_display_name":"Foundation for Innovative Research Groups of the National Natural Science Foundation of China"},{"id":"https://openalex.org/G6270178909","display_name":null,"funder_award_id":"61836009","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320327720","display_name":"Foundation for Innovative Research Groups of the National Natural Science Foundation of China","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":79,"referenced_works":["https://openalex.org/W1496559305","https://openalex.org/W1536680647","https://openalex.org/W1586359073","https://openalex.org/W1902237438","https://openalex.org/W1920235975","https://openalex.org/W1973066300","https://openalex.org/W1978735535","https://openalex.org/W1979341139","https://openalex.org/W1988334140","https://openalex.org/W1994490949","https://openalex.org/W2008374411","https://openalex.org/W2042844016","https://openalex.org/W2064286937","https://openalex.org/W2079299474","https://openalex.org/W2097018403","https://openalex.org/W2099471712","https://openalex.org/W2099582956","https://openalex.org/W2108119513","https://openalex.org/W2115367256","https://openalex.org/W2125614117","https://openalex.org/W2127070009","https://openalex.org/W2129812935","https://openalex.org/W2142026865","https://openalex.org/W2158242013","https://openalex.org/W2173520492","https://openalex.org/W2194775991","https://openalex.org/W2243729554","https://openalex.org/W2288628559","https://openalex.org/W2295763703","https://openalex.org/W2344345011","https://openalex.org/W2345055757","https://openalex.org/W2397078533","https://openalex.org/W2554643804","https://openalex.org/W2579277680","https://openalex.org/W2582131889","https://openalex.org/W2596506150","https://openalex.org/W2615263668","https://openalex.org/W2754361766","https://openalex.org/W2768038465","https://openalex.org/W2779850592","https://openalex.org/W2791890028","https://openalex.org/W2792210438","https://openalex.org/W2804824750","https://openalex.org/W2884853940","https://openalex.org/W2884980254","https://openalex.org/W2897283027","https://openalex.org/W2897760800","https://openalex.org/W2910641067","https://openalex.org/W2915359112","https://openalex.org/W2939196249","https://openalex.org/W2941960459","https://openalex.org/W2942170965","https://openalex.org/W2943216879","https://openalex.org/W2952673310","https://openalex.org/W2961699889","https://openalex.org/W2962695743","https://openalex.org/W2962808998","https://openalex.org/W2962891704","https://openalex.org/W2963032576","https://openalex.org/W2963046541","https://openalex.org/W2963684088","https://openalex.org/W2963685207","https://openalex.org/W2964081807","https://openalex.org/W2964105113","https://openalex.org/W2964166828","https://openalex.org/W4289751869","https://openalex.org/W4297798428","https://openalex.org/W4320013936","https://openalex.org/W6629606793","https://openalex.org/W6634990715","https://openalex.org/W6674642818","https://openalex.org/W6685352114","https://openalex.org/W6714590955","https://openalex.org/W6714644935","https://openalex.org/W6732943021","https://openalex.org/W6740164494","https://openalex.org/W6749351710","https://openalex.org/W6753934646","https://openalex.org/W6755875945"],"related_works":["https://openalex.org/W2766604260","https://openalex.org/W2986507176","https://openalex.org/W3160711233","https://openalex.org/W4220996320","https://openalex.org/W3018421652","https://openalex.org/W2889079306","https://openalex.org/W2996856019","https://openalex.org/W2470368200","https://openalex.org/W2912288872","https://openalex.org/W3160224718"],"abstract_inverted_index":{"Synthetic":[0],"aperture":[1],"radar":[2],"(SAR)":[3],"image":[4,12,30],"classification":[5,38,86,110,175],"is":[6,56,75,118],"a":[7,35,132,161,166],"fundamental":[8],"research":[9],"direction":[10],"in":[11,87,125,135],"interpretation.":[13],"With":[14],"the":[15,42,63,68,78,81,85,88,99,103,115,144,148,152,174,180,187,192],"development":[16],"of":[17,80,98,191],"various":[18],"intelligent":[19],"technologies,":[20],"deep":[21],"learning":[22],"techniques":[23],"are":[24,141,155,169],"gradually":[25],"being":[26],"applied":[27],"to":[28,83,106,120,131,171],"SAR":[29,37,184],"classification.":[31,158],"In":[32,159],"this":[33],"study,":[34],"new":[36,162],"algorithm":[39],"known":[40],"as":[41],"multiscale":[43],"convolutional":[44],"neural":[45],"network":[46,54,104],"with":[47],"an":[48,95,122],"autoencoder":[49,64,73,89,100],"regularization":[50,65,74,90],"joint":[51],"contextual":[52],"attention":[53,70,116,123,128,136,145],"(MCAR-CAN)":[55],"proposed.":[57],"The":[58,138],"MCAR-CAN":[59],"has":[60],"two":[61,153],"branches:":[62],"branch":[66,101],"and":[67,94,165,189],"context":[69,133],"branch.":[71,91,137],"First,":[72],"used":[76,119],"for":[77,157],"reconstruction":[79],"input":[82,93],"regularize":[84],"Multiscale":[92],"asymmetric":[96],"structure":[97],"cause":[102],"more":[105],"be":[107],"focused":[108],"on":[109,112,179],"than":[111],"reconstruction.":[113],"Second,":[114],"mechanism":[117],"produce":[121],"map":[124],"which":[126],"each":[127],"weight":[129],"corresponds":[130],"correlation":[134],"robust":[139],"features":[140,149],"obtained":[142,150],"by":[143,151],"mechanism.":[146],"Finally,":[147],"branches":[154],"spliced":[156],"addition,":[160],"training":[163],"strategy":[164],"postprocessing":[167],"method":[168],"designed":[170],"further":[172],"improve":[173],"accuracy.":[176],"Experiments":[177],"performed":[178],"data":[181],"from":[182],"three":[183],"images":[185],"demonstrated":[186],"effectiveness":[188],"robustness":[190],"proposed":[193],"algorithm.":[194]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":10},{"year":2023,"cited_by_count":8},{"year":2022,"cited_by_count":8},{"year":2021,"cited_by_count":6}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}