{"id":"https://openalex.org/W2779850592","doi":"https://doi.org/10.1109/tgrs.2017.2777868","title":"SAR Image Classification via Deep Recurrent Encoding Neural Networks","display_name":"SAR Image Classification via Deep Recurrent Encoding Neural Networks","publication_year":2017,"publication_date":"2017-12-21","ids":{"openalex":"https://openalex.org/W2779850592","doi":"https://doi.org/10.1109/tgrs.2017.2777868","mag":"2779850592"},"language":"en","primary_location":{"id":"doi:10.1109/tgrs.2017.2777868","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2017.2777868","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/A5033213528","display_name":"Jie Geng","orcid":"https://orcid.org/0000-0003-4858-823X"},"institutions":[{"id":"https://openalex.org/I27357992","display_name":"Dalian University of Technology","ror":"https://ror.org/023hj5876","country_code":"CN","type":"education","lineage":["https://openalex.org/I27357992"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jie Geng","raw_affiliation_strings":["School of Information and Communication Engineering, Dalian University of Technology, Dalian, China"],"raw_orcid":"https://orcid.org/0000-0003-4858-823X","affiliations":[{"raw_affiliation_string":"School of Information and Communication Engineering, Dalian University of Technology, Dalian, China","institution_ids":["https://openalex.org/I27357992"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100422639","display_name":"Hongyu Wang","orcid":"https://orcid.org/0000-0002-1038-412X"},"institutions":[{"id":"https://openalex.org/I27357992","display_name":"Dalian University of Technology","ror":"https://ror.org/023hj5876","country_code":"CN","type":"education","lineage":["https://openalex.org/I27357992"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hongyu Wang","raw_affiliation_strings":["School of Information and Communication Engineering, Dalian University of Technology, Dalian, China"],"raw_orcid":"https://orcid.org/0000-0002-1038-412X","affiliations":[{"raw_affiliation_string":"School of Information and Communication Engineering, Dalian University of Technology, Dalian, China","institution_ids":["https://openalex.org/I27357992"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5089754208","display_name":"Jianchao Fan","orcid":"https://orcid.org/0000-0002-3121-9289"},"institutions":[{"id":"https://openalex.org/I4210114290","display_name":"China National Environmental Monitoring Center","ror":"https://ror.org/026drga03","country_code":"CN","type":"facility","lineage":["https://openalex.org/I204710742","https://openalex.org/I4210114290"]},{"id":"https://openalex.org/I4387156115","display_name":"National Marine Environmental Monitoring Center","ror":"https://ror.org/03eg88604","country_code":null,"type":"facility","lineage":["https://openalex.org/I4387156115"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jianchao Fan","raw_affiliation_strings":["Department of Ocean Remote Sensing, National Marine Environmental Monitoring Center, Dalian, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Ocean Remote Sensing, National Marine Environmental Monitoring Center, Dalian, China","institution_ids":["https://openalex.org/I4210114290","https://openalex.org/I4387156115"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5087248518","display_name":"Xiaorui Ma","orcid":"https://orcid.org/0000-0001-7697-2285"},"institutions":[{"id":"https://openalex.org/I27357992","display_name":"Dalian University of Technology","ror":"https://ror.org/023hj5876","country_code":"CN","type":"education","lineage":["https://openalex.org/I27357992"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaorui Ma","raw_affiliation_strings":["School of Information and Communication Engineering, Dalian University of Technology, Dalian, China"],"raw_orcid":"https://orcid.org/0000-0001-7697-2285","affiliations":[{"raw_affiliation_string":"School of Information and Communication Engineering, Dalian University of Technology, Dalian, China","institution_ids":["https://openalex.org/I27357992"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":2645,"currency":"USD","value_usd":2645},"apc_paid":null,"fwci":126.3,"has_fulltext":false,"cited_by_count":79,"citation_normalized_percentile":{"value":0.99895202,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":100},"biblio":{"volume":"56","issue":"4","first_page":"2255","last_page":"2269"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11038","display_name":"Advanced SAR Imaging 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/T11038","display_name":"Advanced SAR Imaging 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/T10801","display_name":"Synthetic Aperture Radar (SAR) Applications and Techniques","score":0.9991999864578247,"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/T11698","display_name":"Underwater Acoustics Research","score":0.9957000017166138,"subfield":{"id":"https://openalex.org/subfields/1910","display_name":"Oceanography"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7811123132705688},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7512767314910889},{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.7196003198623657},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6994917988777161},{"id":"https://openalex.org/keywords/synthetic-aperture-radar","display_name":"Synthetic aperture radar","score":0.6980239748954773},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.6585431694984436},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.6010180711746216},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5848531723022461},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5578311681747437},{"id":"https://openalex.org/keywords/encoding","display_name":"Encoding (memory)","score":0.5037779211997986},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4965899586677551},{"id":"https://openalex.org/keywords/constraint","display_name":"Constraint (computer-aided design)","score":0.43129387497901917},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4263717532157898},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.4168817400932312},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.37220299243927},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.09339159727096558}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7811123132705688},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7512767314910889},{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.7196003198623657},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6994917988777161},{"id":"https://openalex.org/C87360688","wikidata":"https://www.wikidata.org/wiki/Q740686","display_name":"Synthetic aperture radar","level":2,"score":0.6980239748954773},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.6585431694984436},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.6010180711746216},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5848531723022461},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5578311681747437},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.5037779211997986},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4965899586677551},{"id":"https://openalex.org/C2776036281","wikidata":"https://www.wikidata.org/wiki/Q48769818","display_name":"Constraint (computer-aided design)","level":2,"score":0.43129387497901917},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4263717532157898},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.4168817400932312},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.37220299243927},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.09339159727096558},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tgrs.2017.2777868","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2017.2777868","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":[{"id":"https://metadata.un.org/sdg/10","score":0.6600000262260437,"display_name":"Reduced inequalities"}],"awards":[{"id":"https://openalex.org/G1500189215","display_name":"\u9ad8\u5149\u8c31\u4e0e\u6781\u5316SAR\u56fe\u50cf\u534f\u540c\u6df1\u5ea6\u5b66\u4e60\u5206\u7c7b\u65b9\u6cd5\u7814\u7a76","funder_award_id":"61671103","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G1655372983","display_name":null,"funder_award_id":"DUT17RC(3)024","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"},{"id":"https://openalex.org/G2404842567","display_name":null,"funder_award_id":"2016YFC1401007","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program 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/F4320335777","display_name":"National Key Research and Development Program of China","ror":null},{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":50,"referenced_works":["https://openalex.org/W1583106483","https://openalex.org/W1899504021","https://openalex.org/W1920235975","https://openalex.org/W1950788856","https://openalex.org/W1955857676","https://openalex.org/W1973066300","https://openalex.org/W1979213074","https://openalex.org/W1979341139","https://openalex.org/W1994490949","https://openalex.org/W2000359198","https://openalex.org/W2015861736","https://openalex.org/W2030728252","https://openalex.org/W2049061912","https://openalex.org/W2052190325","https://openalex.org/W2062059528","https://openalex.org/W2064675550","https://openalex.org/W2067193631","https://openalex.org/W2069120802","https://openalex.org/W2076063813","https://openalex.org/W2079299474","https://openalex.org/W2099582956","https://openalex.org/W2115367256","https://openalex.org/W2130111708","https://openalex.org/W2136922672","https://openalex.org/W2151983721","https://openalex.org/W2153635508","https://openalex.org/W2158242013","https://openalex.org/W2170942820","https://openalex.org/W2187089797","https://openalex.org/W2189422931","https://openalex.org/W2243729554","https://openalex.org/W2257307118","https://openalex.org/W2345852998","https://openalex.org/W2397078533","https://openalex.org/W2410591237","https://openalex.org/W2412588858","https://openalex.org/W2431738724","https://openalex.org/W2492018752","https://openalex.org/W2554643804","https://openalex.org/W2559324447","https://openalex.org/W2574739416","https://openalex.org/W2578577414","https://openalex.org/W2580887345","https://openalex.org/W2582131889","https://openalex.org/W2737897717","https://openalex.org/W2919115771","https://openalex.org/W6639569935","https://openalex.org/W6640754710","https://openalex.org/W6665811369","https://openalex.org/W6996569244"],"related_works":["https://openalex.org/W2891059443","https://openalex.org/W2983142544","https://openalex.org/W4281663961","https://openalex.org/W3208888551","https://openalex.org/W4220682630","https://openalex.org/W4313561566","https://openalex.org/W3208386644","https://openalex.org/W3181622257","https://openalex.org/W3133533225","https://openalex.org/W3163146846"],"abstract_inverted_index":{"Synthetic":[0],"aperture":[1],"radar":[2],"(SAR)":[3],"image":[4,12,40,57,105],"classification":[5,41,51,60,186,214],"is":[6,62,72,94,201],"a":[7,84],"fundamental":[8],"process":[9],"for":[10,37],"SAR":[11,28,39,56,101,194,209],"understanding":[13],"and":[14,30,68,112,125,138,145,211],"interpretation.":[15],"With":[16],"the":[17,54,118,134,155,158,166,176,185,198],"advancement":[18],"of":[19,100,136,157,171,180],"imaging":[20],"techniques,":[21],"it":[22],"permits":[23],"to":[24,58,64,96,116,132,153,183,203,216],"produce":[25,212],"higher":[26],"resolution":[27],"data":[29,32],"extend":[31],"amount.":[33],"Therefore,":[34],"intelligent":[35],"algorithms":[36],"high-resolution":[38],"are":[42,107,130,148],"demanded.":[43],"Inspired":[44],"by":[45],"deep":[46,74],"learning":[47,87,169],"technology,":[48],"an":[49],"end-to-end":[50],"model":[52],"from":[53,208],"original":[55],"final":[59,140],"map":[61],"developed":[63,95,149],"automatically":[65],"extract":[66,97],"features":[67,137],"conduct":[69,139],"classification,":[70,141],"which":[71],"named":[73],"recurrent":[75],"encoding":[76],"neural":[77],"networks":[78],"(DRENNs).":[79],"In":[80],"our":[81,181],"proposed":[82,131,199],"framework,":[83],"spatial":[85,120,167],"feature":[86,168,206],"network":[88],"based":[89],"on":[90,192],"long-short-term":[91],"memory":[92],"(LSTM)":[93],"contextual":[98],"dependencies":[99],"images,":[102],"where":[103,142],"2-D":[104],"patches":[106],"transformed":[108],"into":[109,114],"1-D":[110],"sequences":[111],"imported":[113],"LSTM":[115,172],"learn":[117,204],"latent":[119],"correlations.":[121],"After":[122],"LSTM,":[123],"nonnegative":[124,143],"Fisher":[126,146],"constrained":[127],"autoencoders":[128],"(NFCAEs)":[129],"improve":[133,184],"discrimination":[135],"constraint":[144,147],"in":[150],"each":[151],"autoencoder":[152],"restrict":[154],"training":[156],"network.":[159],"The":[160,188],"whole":[161],"DRENN":[162,200],"not":[163],"only":[164],"combines":[165],"power":[170],"but":[173],"also":[174],"utilizes":[175],"discriminative":[177],"representation":[178],"ability":[179],"NFCAE":[182],"performance.":[187],"experimental":[189],"results":[190],"tested":[191],"three":[193],"images":[195,210],"demonstrate":[196],"that":[197],"able":[202],"effective":[205],"representations":[207],"competitive":[213],"accuracies":[215],"other":[217],"related":[218],"approaches.":[219]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":11},{"year":2022,"cited_by_count":10},{"year":2021,"cited_by_count":11},{"year":2020,"cited_by_count":16},{"year":2019,"cited_by_count":14},{"year":2018,"cited_by_count":4}],"updated_date":"2026-08-21T09:56:20.448147","created_date":"2025-10-10T00:00:00"}
