{"id":"https://openalex.org/W4402262169","doi":"https://doi.org/10.1109/igarss53475.2024.10641051","title":"CNN-Enhanced Deep Sparse Representation Network for Polarimetric SAR Image Classification","display_name":"CNN-Enhanced Deep Sparse Representation Network for Polarimetric SAR Image Classification","publication_year":2024,"publication_date":"2024-07-07","ids":{"openalex":"https://openalex.org/W4402262169","doi":"https://doi.org/10.1109/igarss53475.2024.10641051"},"language":"en","primary_location":{"id":"doi:10.1109/igarss53475.2024.10641051","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss53475.2024.10641051","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium","raw_type":"proceedings-article"},"type":"conference-paper","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/A5064627220","display_name":"Junfei Shi","orcid":"https://orcid.org/0000-0002-1603-7698"},"institutions":[{"id":"https://openalex.org/I4210131919","display_name":"Xi'an University of Technology","ror":"https://ror.org/038avdt50","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210131919"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Junfei Shi","raw_affiliation_strings":["Xi&#x2019;an University of Technology,Shaanxi Key Laboratory for Network Computing and Security Technology,Department of Computer Science and Technology,Xi&#x2019;an,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Xi&#x2019;an University of Technology,Shaanxi Key Laboratory for Network Computing and Security Technology,Department of Computer Science and Technology,Xi&#x2019;an,China","institution_ids":["https://openalex.org/I4210131919"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5109662916","display_name":"Mengmeng Nie","orcid":null},"institutions":[{"id":"https://openalex.org/I4210131919","display_name":"Xi'an University of Technology","ror":"https://ror.org/038avdt50","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210131919"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Mengmeng Nie","raw_affiliation_strings":["Xi&#x2019;an University of Technology,Shaanxi Key Laboratory for Network Computing and Security Technology,Department of Computer Science and Technology,Xi&#x2019;an,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Xi&#x2019;an University of Technology,Shaanxi Key Laboratory for Network Computing and Security Technology,Department of Computer Science and Technology,Xi&#x2019;an,China","institution_ids":["https://openalex.org/I4210131919"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5010131867","display_name":"Haiyan Jin","orcid":"https://orcid.org/0000-0003-3742-4029"},"institutions":[{"id":"https://openalex.org/I4210131919","display_name":"Xi'an University of Technology","ror":"https://ror.org/038avdt50","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210131919"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haiyan Jin","raw_affiliation_strings":["Xi&#x2019;an University of Technology,Shaanxi Key Laboratory for Network Computing and Security Technology,Department of Computer Science and Technology,Xi&#x2019;an,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Xi&#x2019;an University of Technology,Shaanxi Key Laboratory for Network Computing and Security Technology,Department of Computer Science and Technology,Xi&#x2019;an,China","institution_ids":["https://openalex.org/I4210131919"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112407377","display_name":"Junhuai Li","orcid":null},"institutions":[{"id":"https://openalex.org/I4210131919","display_name":"Xi'an University of Technology","ror":"https://ror.org/038avdt50","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210131919"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Junhuai Li","raw_affiliation_strings":["Xi&#x2019;an University of Technology,Shaanxi Key Laboratory for Network Computing and Security Technology,Department of Computer Science and Technology,Xi&#x2019;an,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Xi&#x2019;an University of Technology,Shaanxi Key Laboratory for Network Computing and Security Technology,Department of Computer Science and Technology,Xi&#x2019;an,China","institution_ids":["https://openalex.org/I4210131919"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5046450643","display_name":"Yuanlin Zhang","orcid":"https://orcid.org/0000-0003-0960-3636"},"institutions":[{"id":"https://openalex.org/I4210131919","display_name":"Xi'an University of Technology","ror":"https://ror.org/038avdt50","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210131919"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuanlin Zhang","raw_affiliation_strings":["Xi&#x2019;an University of Technology,Shaanxi Key Laboratory for Network Computing and Security Technology,Department of Computer Science and Technology,Xi&#x2019;an,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Xi&#x2019;an University of Technology,Shaanxi Key Laboratory for Network Computing and Security Technology,Department of Computer Science and Technology,Xi&#x2019;an,China","institution_ids":["https://openalex.org/I4210131919"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I4210131919"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"11235","last_page":"11238"},"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":1.0,"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":1.0,"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":0.9997000098228455,"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":0.9994000196456909,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7278279066085815},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7200609445571899},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.58279949426651},{"id":"https://openalex.org/keywords/sparse-approximation","display_name":"Sparse approximation","score":0.5530845522880554},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.5191347002983093},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.4970572292804718},{"id":"https://openalex.org/keywords/synthetic-aperture-radar","display_name":"Synthetic aperture radar","score":0.47208330035209656},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4635322391986847},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4382333755493164},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.43362027406692505},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.4179037809371948},{"id":"https://openalex.org/keywords/radar-imaging","display_name":"Radar imaging","score":0.41183626651763916},{"id":"https://openalex.org/keywords/radar","display_name":"Radar","score":0.14072740077972412},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.06158968806266785}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7278279066085815},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7200609445571899},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.58279949426651},{"id":"https://openalex.org/C124066611","wikidata":"https://www.wikidata.org/wiki/Q28684319","display_name":"Sparse approximation","level":2,"score":0.5530845522880554},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.5191347002983093},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.4970572292804718},{"id":"https://openalex.org/C87360688","wikidata":"https://www.wikidata.org/wiki/Q740686","display_name":"Synthetic aperture radar","level":2,"score":0.47208330035209656},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4635322391986847},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4382333755493164},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.43362027406692505},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.4179037809371948},{"id":"https://openalex.org/C10929652","wikidata":"https://www.wikidata.org/wiki/Q7279985","display_name":"Radar imaging","level":3,"score":0.41183626651763916},{"id":"https://openalex.org/C554190296","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar","level":2,"score":0.14072740077972412},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.06158968806266785},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/igarss53475.2024.10641051","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss53475.2024.10641051","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":7,"referenced_works":["https://openalex.org/W2095456996","https://openalex.org/W2115706991","https://openalex.org/W2559324447","https://openalex.org/W2911586772","https://openalex.org/W4206420443","https://openalex.org/W4387802859","https://openalex.org/W4387802914"],"related_works":["https://openalex.org/W2545123933","https://openalex.org/W2952813363","https://openalex.org/W2585813813","https://openalex.org/W2041414401","https://openalex.org/W2042726296","https://openalex.org/W2096748030","https://openalex.org/W3016428515","https://openalex.org/W2160730947","https://openalex.org/W2747205507","https://openalex.org/W2917196883"],"abstract_inverted_index":{"Deep":[0,64,103],"learning":[1,19,80,124],"networks":[2],"can":[3],"automatically":[4],"acquire":[5],"high-level":[6],"semantic":[7,49,144],"features":[8,47,145],"for":[9,69,89],"polarimetric":[10],"SAR":[11],"image":[12,46,71],"classification,":[13,72],"while":[14],"it":[15],"involves":[16],"a":[17,34,57,74,83,102,120,131],"blind":[18],"procedure":[20,118],"without":[21],"explicit":[22],"guidance.":[23,40],"In":[24],"contrast,":[25],"sparse":[26,84,100,126],"representation":[27,85],"methods":[28],"represent":[29],"effective":[30],"non-deep":[31],"models":[32],"with":[33,138],"robust":[35],"mathematical":[36],"mechanism":[37],"serving":[38],"as":[39,61,128],"However,":[41],"they":[42],"can\u2019t":[43],"capture":[44,93],"complex":[45],"and":[48,146],"information.":[50],"To":[51],"address":[52],"these":[53],"issues,":[54],"we":[55],"propose":[56],"novel":[58],"approach":[59],"known":[60],"the":[62,99,112,152,155],"CNN-enhanced":[63,132],"Sparse":[65,75,104],"Representation":[66,76,105],"Network":[67,106],"(CE-DSRNet)":[68],"PolSAR":[70,90],"which":[73],"(SR)":[77],"guided":[78],"deep":[79,143],"model.":[81],"Initially,":[82],"model":[86],"is":[87,108,134],"constructed":[88],"images":[91],"to":[92,97,140,159],"essential":[94],"features.":[95,129],"Subsequently,":[96],"solve":[98],"model,":[101],"(DSRNet)":[107],"devised":[109],"by":[110],"transforming":[111],"Soft":[113],"Threshold":[114],"Iterative":[115],"(ISTA)":[116],"optimization":[117],"into":[119],"network,":[121],"enabling":[122],"automatic":[123],"of":[125,154],"coefficients":[127],"Finally,":[130],"DSRNet":[133,137],"introduced,":[135],"integrating":[136],"CNN":[139],"effectively":[141],"extract":[142],"enhance":[147],"classification":[148],"accuracy.":[149],"Experiments":[150],"demonstrate":[151],"effectiveness":[153],"proposed":[156],"method":[157],"compared":[158],"state-of-the-art":[160],"approaches.":[161]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
