{"id":"https://openalex.org/W2989067579","doi":"https://doi.org/10.3390/rs11222653","title":"Pixel-Wise PolSAR Image Classification via a Novel Complex-Valued Deep Fully Convolutional Network","display_name":"Pixel-Wise PolSAR Image Classification via a Novel Complex-Valued Deep Fully Convolutional Network","publication_year":2019,"publication_date":"2019-11-13","ids":{"openalex":"https://openalex.org/W2989067579","doi":"https://doi.org/10.3390/rs11222653","mag":"2989067579"},"language":"en","primary_location":{"id":"doi:10.3390/rs11222653","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs11222653","pdf_url":"https://www.mdpi.com/2072-4292/11/22/2653/pdf?version=1573721295","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"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":"Remote Sensing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/2072-4292/11/22/2653/pdf?version=1573721295","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5087038469","display_name":"Yice Cao","orcid":"https://orcid.org/0009-0009-4734-4592"},"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":"Yice Cao","raw_affiliation_strings":["Remote Sensing Image Processing and Fusion Group, School of Electronic Engineering, Xidian University, Xi\u2019an 710071, China","Remote Sensing Image Processing and Fusion Group, School of Electronic Engineering, Xidian University, Xi'an 710071, China"],"affiliations":[{"raw_affiliation_string":"Remote Sensing Image Processing and Fusion Group, School of Electronic Engineering, Xidian University, Xi\u2019an 710071, China","institution_ids":["https://openalex.org/I149594827"]},{"raw_affiliation_string":"Remote Sensing Image Processing and Fusion Group, School of Electronic Engineering, Xidian University, Xi'an 710071, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100620718","display_name":"Yan Wu","orcid":"https://orcid.org/0000-0001-7502-2341"},"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":"Yan Wu","raw_affiliation_strings":["Remote Sensing Image Processing and Fusion Group, School of Electronic Engineering, Xidian University, Xi\u2019an 710071, China","Remote Sensing Image Processing and Fusion Group, School of Electronic Engineering, Xidian University, Xi'an 710071, China"],"affiliations":[{"raw_affiliation_string":"Remote Sensing Image Processing and Fusion Group, School of Electronic Engineering, Xidian University, Xi\u2019an 710071, China","institution_ids":["https://openalex.org/I149594827"]},{"raw_affiliation_string":"Remote Sensing Image Processing and Fusion Group, School of Electronic Engineering, Xidian University, Xi'an 710071, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5088683171","display_name":"Peng Zhang","orcid":"https://orcid.org/0000-0002-8065-0948"},"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":"Peng Zhang","raw_affiliation_strings":["National Laboratory of Radar Signal Processing, Xidian University, Xi\u2019an 710071, China","National Laboratory of Radar Signal Processing, Xidian University, Xi'an 710071, China"],"affiliations":[{"raw_affiliation_string":"National Laboratory of Radar Signal Processing, Xidian University, Xi\u2019an 710071, China","institution_ids":["https://openalex.org/I149594827"]},{"raw_affiliation_string":"National Laboratory of Radar Signal Processing, Xidian University, Xi'an 710071, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5015652605","display_name":"Wenkai Liang","orcid":"https://orcid.org/0000-0003-2936-4564"},"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":"Wenkai Liang","raw_affiliation_strings":["Remote Sensing Image Processing and Fusion Group, School of Electronic Engineering, Xidian University, Xi\u2019an 710071, China","Remote Sensing Image Processing and Fusion Group, School of Electronic Engineering, Xidian University, Xi'an 710071, China"],"affiliations":[{"raw_affiliation_string":"Remote Sensing Image Processing and Fusion Group, School of Electronic Engineering, Xidian University, Xi\u2019an 710071, China","institution_ids":["https://openalex.org/I149594827"]},{"raw_affiliation_string":"Remote Sensing Image Processing and Fusion Group, School of Electronic Engineering, Xidian University, Xi'an 710071, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100662583","display_name":"Ming Li","orcid":"https://orcid.org/0000-0002-4706-5173"},"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":"Ming Li","raw_affiliation_strings":["National Laboratory of Radar Signal Processing, Xidian University, Xi\u2019an 710071, China","National Laboratory of Radar Signal Processing, Xidian University, Xi'an 710071, China"],"affiliations":[{"raw_affiliation_string":"National Laboratory of Radar Signal Processing, Xidian University, Xi\u2019an 710071, China","institution_ids":["https://openalex.org/I149594827"]},{"raw_affiliation_string":"National Laboratory of Radar Signal Processing, Xidian University, Xi'an 710071, China","institution_ids":["https://openalex.org/I149594827"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5100620718"],"corresponding_institution_ids":["https://openalex.org/I149594827"],"apc_list":{"value":2500,"currency":"CHF","value_usd":2707},"apc_paid":{"value":2500,"currency":"CHF","value_usd":2707},"fwci":12.2976,"has_fulltext":false,"cited_by_count":64,"citation_normalized_percentile":{"value":0.98588286,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":"11","issue":"22","first_page":"2653","last_page":"2653"},"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":0.9998999834060669,"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/T10801","display_name":"Synthetic Aperture Radar (SAR) Applications and 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/T11038","display_name":"Advanced SAR Imaging Techniques","score":0.9973000288009644,"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":0.9962000250816345,"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/upsampling","display_name":"Upsampling","score":0.8612015247344971},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.687188982963562},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6823830008506775},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6587839722633362},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.6564277410507202},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.48996415734291077},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.48464542627334595},{"id":"https://openalex.org/keywords/initialization","display_name":"Initialization","score":0.4831251800060272},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.21936708688735962}],"concepts":[{"id":"https://openalex.org/C110384440","wikidata":"https://www.wikidata.org/wiki/Q1143270","display_name":"Upsampling","level":3,"score":0.8612015247344971},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.687188982963562},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6823830008506775},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6587839722633362},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.6564277410507202},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.48996415734291077},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.48464542627334595},{"id":"https://openalex.org/C114466953","wikidata":"https://www.wikidata.org/wiki/Q6034165","display_name":"Initialization","level":2,"score":0.4831251800060272},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.21936708688735962},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.3390/rs11222653","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs11222653","pdf_url":"https://www.mdpi.com/2072-4292/11/22/2653/pdf?version=1573721295","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"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":"Remote Sensing","raw_type":"journal-article"},{"id":"pmh:oai:mdpi.com:/2072-4292/11/22/2653/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/rs11222653","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":"Remote Sensing; Volume 11; Issue 22; Pages: 2653","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/rs11222653","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs11222653","pdf_url":"https://www.mdpi.com/2072-4292/11/22/2653/pdf?version=1573721295","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"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":"Remote Sensing","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities","score":0.7400000095367432}],"awards":[{"id":"https://openalex.org/G3808536429","display_name":null,"funder_award_id":"61871312","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6513085620","display_name":null,"funder_award_id":"61772390","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"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2989067579.pdf","grobid_xml":"https://content.openalex.org/works/W2989067579.grobid-xml"},"referenced_works_count":52,"referenced_works":["https://openalex.org/W1677182931","https://openalex.org/W1849277567","https://openalex.org/W1903029394","https://openalex.org/W1974024703","https://openalex.org/W1985194020","https://openalex.org/W1989757000","https://openalex.org/W1992824785","https://openalex.org/W2000370119","https://openalex.org/W2008826820","https://openalex.org/W2030728252","https://openalex.org/W2048578702","https://openalex.org/W2052190325","https://openalex.org/W2077547750","https://openalex.org/W2078985447","https://openalex.org/W2081144903","https://openalex.org/W2101690226","https://openalex.org/W2105923215","https://openalex.org/W2114578114","https://openalex.org/W2132012856","https://openalex.org/W2133989913","https://openalex.org/W2144554203","https://openalex.org/W2158242013","https://openalex.org/W2170481611","https://openalex.org/W2326827146","https://openalex.org/W2345055757","https://openalex.org/W2395611524","https://openalex.org/W2406273144","https://openalex.org/W2494341560","https://openalex.org/W2559324447","https://openalex.org/W2574739416","https://openalex.org/W2593886839","https://openalex.org/W2616755213","https://openalex.org/W2618946976","https://openalex.org/W2754361766","https://openalex.org/W2764034829","https://openalex.org/W2766299269","https://openalex.org/W2767003110","https://openalex.org/W2770727026","https://openalex.org/W2772082715","https://openalex.org/W2782522152","https://openalex.org/W2789584428","https://openalex.org/W2793268137","https://openalex.org/W2804230435","https://openalex.org/W2804850629","https://openalex.org/W2891282097","https://openalex.org/W2897760800","https://openalex.org/W2904891876","https://openalex.org/W2930359273","https://openalex.org/W2971355295","https://openalex.org/W3105127913","https://openalex.org/W6640054144","https://openalex.org/W6767015584"],"related_works":["https://openalex.org/W2062399876","https://openalex.org/W3204184292","https://openalex.org/W2607795551","https://openalex.org/W3176564347","https://openalex.org/W1985458517","https://openalex.org/W2355833770","https://openalex.org/W3155117723","https://openalex.org/W1991429770","https://openalex.org/W1983892167","https://openalex.org/W3031039437"],"abstract_inverted_index":{"Although":[0],"complex-valued":[1,43,111],"(CV)":[2],"neural":[3,47],"networks":[4,28],"have":[5],"shown":[6],"better":[7,193,257],"classification":[8,235,258],"results":[9],"compared":[10],"to":[11,29,85,117,127,145,175,186,195,227],"their":[12],"real-valued":[13],"(RV)":[14],"counterparts":[15],"for":[16,51,103,192,245],"polarimetric":[17,88],"synthetic":[18],"aperture":[19],"radar":[20],"(PolSAR)":[21],"classification,":[22],"the":[23,30,63,68,92,99,104,122,164,182,203,206,215,221],"extension":[24],"of":[25,106,124,209],"pixel-level":[26,74],"RV":[27],"complex":[31,142,165,170,183,199,210,222],"domain":[32],"has":[33],"not":[34],"yet":[35],"thoroughly":[36],"examined.":[37],"This":[38],"paper":[39],"presents":[40],"a":[41,109,141,169,237],"novel":[42,238],"deep":[44,69],"fully":[45],"convolutional":[46],"network":[48],"(CV-FCN)":[49],"designed":[50],"PolSAR":[52,58,94,107,251],"image":[53,95],"classification.":[54],"Specifically,":[55],"CV-FCN":[56,77,129,139,246,255],"uses":[57,67],"CV":[59,154,178],"data":[60,126],"that":[61,72,156,254],"includes":[62],"phase":[64],"information":[65,160,191],"and":[66,90,136,205,231],"FCN":[70],"architecture":[71,78],"performs":[73],"labeling.":[75,179],"The":[76,198],"is":[79,96,115,173,243],"trained":[80,100],"in":[81,133],"an":[82,134],"end-to-end":[83],"scheme":[84,114,144,172],"extract":[86,146],"discriminative":[87,151],"features,":[89],"then":[91],"entire":[93],"classified":[97],"by":[98],"CV-FCN.":[101,119],"Technically,":[102],"particularity":[105],"data,":[108],"dedicated":[110],"weight":[112],"initialization":[113],"proposed":[116,174],"initialize":[118],"It":[120,180],"considers":[121],"distribution":[123],"polarization":[125,159],"conduct":[128],"training":[130],"from":[131,220],"scratch":[132],"efficient":[135],"fast":[137],"manner.":[138],"employs":[140,181],"downsampling-then-upsampling":[143],"dense":[147,177],"features.":[148],"To":[149],"enrich":[150],"information,":[152],"multi-level":[153],"features":[155],"retain":[157],"more":[158,189,233],"are":[161],"extracted":[162],"via":[163],"downsampling":[166,223],"scheme.":[167,224],"Then,":[168],"upsampling":[171],"predict":[176],"max-unpooling":[184,200],"layers":[185,201],"greatly":[187],"capture":[188],"spatial":[190],"robustness":[194],"speckle":[196],"noise.":[197],"upsample":[202],"real":[204,250],"imaginary":[207],"parts":[208],"feature":[211],"maps":[212,218],"based":[213],"on":[214,249],"max":[216],"locations":[217],"retained":[219],"In":[225],"addition,":[226],"achieve":[228],"faster":[229],"convergence":[230],"obtain":[232],"precise":[234],"results,":[236],"average":[239],"cross-entropy":[240],"loss":[241],"function":[242],"derived":[244],"optimization.":[247],"Experiments":[248],"datasets":[252],"demonstrate":[253],"achieves":[256],"performance":[259],"than":[260],"other":[261],"state-of-art":[262],"methods.":[263]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":10},{"year":2024,"cited_by_count":9},{"year":2023,"cited_by_count":12},{"year":2022,"cited_by_count":10},{"year":2021,"cited_by_count":13},{"year":2020,"cited_by_count":8}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
