{"id":"https://openalex.org/W3012261719","doi":"https://doi.org/10.3390/s20051533","title":"A Multi-Scale U-Shaped Convolution Auto-Encoder Based on Pyramid Pooling Module for Object Recognition in Synthetic Aperture Radar Images","display_name":"A Multi-Scale U-Shaped Convolution Auto-Encoder Based on Pyramid Pooling Module for Object Recognition in Synthetic Aperture Radar Images","publication_year":2020,"publication_date":"2020-03-10","ids":{"openalex":"https://openalex.org/W3012261719","doi":"https://doi.org/10.3390/s20051533","mag":"3012261719","pmid":"https://pubmed.ncbi.nlm.nih.gov/32164293"},"language":"en","primary_location":{"id":"doi:10.3390/s20051533","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s20051533","pdf_url":"https://www.mdpi.com/1424-8220/20/5/1533/pdf?version=1584012388","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/1424-8220/20/5/1533/pdf?version=1584012388","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5020900169","display_name":"Sirui Tian","orcid":"https://orcid.org/0000-0003-3601-6189"},"institutions":[{"id":"https://openalex.org/I36399199","display_name":"Nanjing University of Science and Technology","ror":"https://ror.org/00xp9wg62","country_code":"CN","type":"education","lineage":["https://openalex.org/I36399199"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Sirui Tian","raw_affiliation_strings":["Department of Electronic Engineering, School of Electronic and Optical Engineering, Nanjing University of Science and Technology, Nanjing 210094, China"],"raw_orcid":"https://orcid.org/0000-0003-3601-6189","affiliations":[{"raw_affiliation_string":"Department of Electronic Engineering, School of Electronic and Optical Engineering, Nanjing University of Science and Technology, Nanjing 210094, China","institution_ids":["https://openalex.org/I36399199"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5025625731","display_name":"Yiyu Lin","orcid":"https://orcid.org/0000-0002-9267-4138"},"institutions":[{"id":"https://openalex.org/I103635307","display_name":"University of California, Riverside","ror":"https://ror.org/03nawhv43","country_code":"US","type":"education","lineage":["https://openalex.org/I103635307"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yiyu Lin","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of California, Riverside, Riversidem, CA 92521, USA"],"raw_orcid":"https://orcid.org/0000-0002-9267-4138","affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of California, Riverside, Riversidem, CA 92521, USA","institution_ids":["https://openalex.org/I103635307"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5058386162","display_name":"Wenyun Gao","orcid":"https://orcid.org/0000-0003-4911-962X"},"institutions":[{"id":"https://openalex.org/I163340411","display_name":"Hohai University","ror":"https://ror.org/01wd4xt90","country_code":"CN","type":"education","lineage":["https://openalex.org/I163340411"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenyun Gao","raw_affiliation_strings":["College of Computer and Information, Hohai University, Nanjing 211100, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Computer and Information, Hohai University, Nanjing 211100, China","institution_ids":["https://openalex.org/I163340411"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100430255","display_name":"Hong Zhang","orcid":"https://orcid.org/0000-0002-0088-8148"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210128053","display_name":"Institute of Remote Sensing and Digital Earth","ror":"https://ror.org/02cjszf03","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210128053"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hong Zhang","raw_affiliation_strings":["Key Laboratory of Digital Earth Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100094, China"],"raw_orcid":"https://orcid.org/0000-0002-0088-8148","affiliations":[{"raw_affiliation_string":"Key Laboratory of Digital Earth Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100094, China","institution_ids":["https://openalex.org/I19820366","https://openalex.org/I4210128053"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5115076700","display_name":"Chao Wang","orcid":"https://orcid.org/0000-0003-4887-923X"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210128053","display_name":"Institute of Remote Sensing and Digital Earth","ror":"https://ror.org/02cjszf03","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210128053"]},{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chao Wang","raw_affiliation_strings":["College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China","Key Laboratory of Digital Earth Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100094, China"],"raw_orcid":"https://orcid.org/0000-0003-4887-923X","affiliations":[{"raw_affiliation_string":"College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China","institution_ids":["https://openalex.org/I4210165038"]},{"raw_affiliation_string":"Key Laboratory of Digital Earth Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100094, China","institution_ids":["https://openalex.org/I19820366","https://openalex.org/I4210128053"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5020900169"],"corresponding_institution_ids":["https://openalex.org/I36399199"],"apc_list":{"value":2400,"currency":"CHF","value_usd":2673},"apc_paid":{"value":2400,"currency":"CHF","value_usd":2673},"fwci":8.5038,"has_fulltext":true,"cited_by_count":8,"citation_normalized_percentile":{"value":0.97225934,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"20","issue":"5","first_page":"1533","last_page":"1533"},"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/T11609","display_name":"Geophysical Methods and Applications","score":0.9994000196456909,"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"}},{"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"}}],"keywords":[{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7685648202896118},{"id":"https://openalex.org/keywords/synthetic-aperture-radar","display_name":"Synthetic aperture radar","score":0.6976116895675659},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6468578577041626},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.6124371290206909},{"id":"https://openalex.org/keywords/speckle-pattern","display_name":"Speckle pattern","score":0.6072285771369934},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5845333933830261},{"id":"https://openalex.org/keywords/pyramid","display_name":"Pyramid (geometry)","score":0.5296199917793274},{"id":"https://openalex.org/keywords/pooling","display_name":"Pooling","score":0.5050624012947083},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4976947605609894},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4866076707839966},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.44799888134002686},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.4261632561683655},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.4193033277988434},{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.4175027012825012},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.4126441180706024},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.29152894020080566},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.1729152500629425},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.15039777755737305},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.14030689001083374}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7685648202896118},{"id":"https://openalex.org/C87360688","wikidata":"https://www.wikidata.org/wiki/Q740686","display_name":"Synthetic aperture radar","level":2,"score":0.6976116895675659},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6468578577041626},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.6124371290206909},{"id":"https://openalex.org/C102290492","wikidata":"https://www.wikidata.org/wiki/Q7575045","display_name":"Speckle pattern","level":2,"score":0.6072285771369934},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5845333933830261},{"id":"https://openalex.org/C142575187","wikidata":"https://www.wikidata.org/wiki/Q3358290","display_name":"Pyramid (geometry)","level":2,"score":0.5296199917793274},{"id":"https://openalex.org/C70437156","wikidata":"https://www.wikidata.org/wiki/Q7228652","display_name":"Pooling","level":2,"score":0.5050624012947083},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4976947605609894},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4866076707839966},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.44799888134002686},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.4261632561683655},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.4193033277988434},{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.4175027012825012},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.4126441180706024},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.29152894020080566},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.1729152500629425},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.15039777755737305},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.14030689001083374},{"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/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":5,"locations":[{"id":"doi:10.3390/s20051533","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s20051533","pdf_url":"https://www.mdpi.com/1424-8220/20/5/1533/pdf?version=1584012388","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},{"id":"pmid:32164293","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/32164293","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors (Basel, Switzerland)","raw_type":null},{"id":"pmh:oai:europepmc.org:6042074","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/7085543","pdf_url":null,"source":{"id":"https://openalex.org/S4306400806","display_name":"Europe PMC (PubMed Central)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1303153112","host_organization_name":"European Bioinformatics Institute","host_organization_lineage":["https://openalex.org/I1303153112"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Text"},{"id":"pmh:oai:doaj.org/article:af44b33caa164420b3b0ec22aaea27f9","is_oa":true,"landing_page_url":"https://doaj.org/article/af44b33caa164420b3b0ec22aaea27f9","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Sensors, Vol 20, Iss 5, p 1533 (2020)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/1424-8220/20/5/1533/","is_oa":true,"landing_page_url":"http://dx.doi.org/10.3390/s20051533","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Sensors","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/s20051533","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s20051533","pdf_url":"https://www.mdpi.com/1424-8220/20/5/1533/pdf?version=1584012388","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.7200000286102295,"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities"}],"awards":[{"id":"https://openalex.org/G8882528501","display_name":null,"funder_award_id":"BK20150774","funder_id":"https://openalex.org/F4320322769","funder_display_name":"Natural Science Foundation of Jiangsu Province"}],"funders":[{"id":"https://openalex.org/F4320321605","display_name":"Government of Jiangsu Province","ror":"https://ror.org/004svx814"},{"id":"https://openalex.org/F4320322769","display_name":"Natural Science Foundation of Jiangsu Province","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320332467","display_name":"U.S. Air Force","ror":"https://ror.org/006gmme17"},{"id":"https://openalex.org/F4320338294","display_name":"Air Force Research Laboratory","ror":"https://ror.org/02e2egq70"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3012261719.pdf","grobid_xml":"https://content.openalex.org/works/W3012261719.grobid-xml"},"referenced_works_count":65,"referenced_works":["https://openalex.org/W204464906","https://openalex.org/W1558921750","https://openalex.org/W1635144632","https://openalex.org/W1677182931","https://openalex.org/W1686810756","https://openalex.org/W1920235975","https://openalex.org/W2064108454","https://openalex.org/W2065337811","https://openalex.org/W2071379627","https://openalex.org/W2089520361","https://openalex.org/W2106608684","https://openalex.org/W2109255472","https://openalex.org/W2111847198","https://openalex.org/W2129038850","https://openalex.org/W2133665775","https://openalex.org/W2162931300","https://openalex.org/W2269648248","https://openalex.org/W2270280304","https://openalex.org/W2292481059","https://openalex.org/W2304648132","https://openalex.org/W2327366155","https://openalex.org/W2345852998","https://openalex.org/W2410591237","https://openalex.org/W2492018752","https://openalex.org/W2531409750","https://openalex.org/W2536954809","https://openalex.org/W2544339223","https://openalex.org/W2578577414","https://openalex.org/W2588453093","https://openalex.org/W2588677815","https://openalex.org/W2596473454","https://openalex.org/W2597000936","https://openalex.org/W2610921225","https://openalex.org/W2728628784","https://openalex.org/W2752788177","https://openalex.org/W2756157229","https://openalex.org/W2765832304","https://openalex.org/W2766299269","https://openalex.org/W2770727026","https://openalex.org/W2771921445","https://openalex.org/W2783573226","https://openalex.org/W2790279720","https://openalex.org/W2804451427","https://openalex.org/W2806263990","https://openalex.org/W2883543868","https://openalex.org/W2890212406","https://openalex.org/W2893196123","https://openalex.org/W2894660140","https://openalex.org/W2918419857","https://openalex.org/W2939600327","https://openalex.org/W2944003962","https://openalex.org/W2944029760","https://openalex.org/W2948594896","https://openalex.org/W2962812282","https://openalex.org/W2962835968","https://openalex.org/W2965381371","https://openalex.org/W2968800899","https://openalex.org/W2984890934","https://openalex.org/W2988368429","https://openalex.org/W2996093102","https://openalex.org/W3122279293","https://openalex.org/W4231109964","https://openalex.org/W6631190155","https://openalex.org/W6636725746","https://openalex.org/W6678903991"],"related_works":["https://openalex.org/W2022849497","https://openalex.org/W3081299480","https://openalex.org/W2407190427","https://openalex.org/W2919210741","https://openalex.org/W2907584218","https://openalex.org/W3002446410","https://openalex.org/W2983142544","https://openalex.org/W4390224712","https://openalex.org/W4322096758","https://openalex.org/W2891059443"],"abstract_inverted_index":{"Although":[0],"unsupervised":[1,44],"representation":[2],"learning":[3,94,166],"(RL)":[4],"can":[5,35,52],"tackle":[6],"the":[7,22,28,55,78,85,91,111,117,122,129,133,137,150,156,164,171,175,185,188],"performance":[8,38],"deterioration":[9],"caused":[10],"by":[11,121,136],"limited":[12],"labeled":[13],"data":[14,131],"in":[15,110,149,163,191],"synthetic":[16],"aperture":[17],"radar":[18],"(SAR)":[19],"object":[20,193],"classification,":[21],"neglected":[23],"discriminative":[24],"detailed":[25],"information":[26],"and":[27,58,67,77,90,132,179],"ignored":[29],"distinctive":[30],"characteristics":[31,60],"of":[32,61,104,116,128,187],"SAR":[33,105,192],"images":[34,134],"lead":[36],"to":[37,83,98,153],"degradation.":[39],"In":[40],"this":[41],"paper,":[42],"an":[43],"multi-scale":[45,92,100],"convolution":[46,76],"auto-encoder":[47],"(MSCAE)":[48],"was":[49,107,119,146],"proposed":[50,189],"which":[51],"simultaneously":[53],"obtain":[54],"global":[56],"features":[57],"local":[59],"targets":[62],"with":[63,170],"its":[64],"U-shaped":[65],"architecture":[66],"pyramid":[68],"pooling":[69],"modules":[70],"(PPMs).":[71],"The":[72,88,113],"compact":[73],"depth-wise":[74],"separable":[75],"deconvolution":[79],"counterpart":[80],"were":[81,96],"devised":[82],"decrease":[84],"trainable":[86],"parameters.":[87],"PPM":[89],"feature":[93,165],"scheme":[95],"designed":[97],"learn":[99],"features.":[101],"Prior":[102],"knowledge":[103],"speckle":[106,143,157],"also":[108,147],"embedded":[109],"model.":[112],"reconstruction":[114],"loss":[115],"MSCAE":[118],"measured":[120],"structural":[123],"similarity":[124],"index":[125],"metric":[126],"(SSIM)":[127],"reconstructed":[130],"filtered":[135],"improved":[138],"Lee":[139],"sigma":[140],"filter.":[141],"A":[142],"suppression":[144,158],"restriction":[145],"added":[148],"objective":[151],"function":[152],"guarantee":[154],"that":[155],"procedure":[159],"would":[160],"take":[161],"place":[162],"stage.":[167],"Experimental":[168],"results":[169],"MSTAR":[172],"dataset":[173],"under":[174],"standard":[176],"operating":[177,182],"condition":[178],"several":[180],"extended":[181],"conditions":[183],"demonstrated":[184],"effectiveness":[186],"model":[190],"classification":[194],"tasks.":[195]},"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":1},{"year":2020,"cited_by_count":1}],"updated_date":"2026-08-13T07:04:57.449891","created_date":"2025-10-10T00:00:00"}
