{"id":"https://openalex.org/W4327521558","doi":"https://doi.org/10.1109/lgrs.2023.3257412","title":"SM-CNN: Separability Measure-Based CNN for SAR Target Recognition","display_name":"SM-CNN: Separability Measure-Based CNN for SAR Target Recognition","publication_year":2023,"publication_date":"2023-01-01","ids":{"openalex":"https://openalex.org/W4327521558","doi":"https://doi.org/10.1109/lgrs.2023.3257412"},"language":"en","primary_location":{"id":"doi:10.1109/lgrs.2023.3257412","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lgrs.2023.3257412","pdf_url":null,"source":{"id":"https://openalex.org/S126920919","display_name":"IEEE Geoscience and Remote Sensing Letters","issn_l":"1545-598X","issn":["1545-598X","1558-0571"],"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 Geoscience and Remote Sensing Letters","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/A5100376949","display_name":"Yifan Zhang","orcid":"https://orcid.org/0000-0002-8549-7305"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yifan Zhang","raw_affiliation_strings":["School of Electronic Science, School of Information Communication, National University of Defense Technology, Changsha, China"],"affiliations":[{"raw_affiliation_string":"School of Electronic Science, School of Information Communication, National University of Defense Technology, Changsha, China","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5078507701","display_name":"Jingyuan Xia","orcid":"https://orcid.org/0000-0003-4329-0354"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jingyuan Xia","raw_affiliation_strings":["School of Electronic Science, School of Information Communication, National University of Defense Technology, Changsha, China"],"affiliations":[{"raw_affiliation_string":"School of Electronic Science, School of Information Communication, National University of Defense Technology, Changsha, China","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112128567","display_name":"Xunzhang Gao","orcid":null},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xunzhang Gao","raw_affiliation_strings":["School of Electronic Science, School of Information Communication, National University of Defense Technology, Changsha, China"],"affiliations":[{"raw_affiliation_string":"School of Electronic Science, School of Information Communication, National University of Defense Technology, Changsha, China","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5011746519","display_name":"Lingyan Xue","orcid":null},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lingyan Xue","raw_affiliation_strings":["School of Electronic Science, School of Information Communication, National University of Defense Technology, Changsha, China"],"affiliations":[{"raw_affiliation_string":"School of Electronic Science, School of Information Communication, National University of Defense Technology, Changsha, China","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5006172988","display_name":"Xinyu Zhang","orcid":"https://orcid.org/0000-0002-6807-049X"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xinyu Zhang","raw_affiliation_strings":["School of Electronic Science, School of Information Communication, National University of Defense Technology, Changsha, China"],"affiliations":[{"raw_affiliation_string":"School of Electronic Science, School of Information Communication, National University of Defense Technology, Changsha, China","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100331131","display_name":"Xiang Li","orcid":"https://orcid.org/0000-0003-4383-6505"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiang Li","raw_affiliation_strings":["School of Electronic Science, School of Information Communication, National University of Defense Technology, Changsha, China"],"affiliations":[{"raw_affiliation_string":"School of Electronic Science, School of Information Communication, National University of Defense Technology, Changsha, China","institution_ids":["https://openalex.org/I170215575"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5100376949"],"corresponding_institution_ids":["https://openalex.org/I170215575"],"apc_list":null,"apc_paid":null,"fwci":15.6468,"has_fulltext":false,"cited_by_count":19,"citation_normalized_percentile":{"value":0.98540146,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":99},"biblio":{"volume":"20","issue":null,"first_page":"1","last_page":"5"},"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":0.9962999820709229,"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":0.9921000003814697,"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":0.7496102452278137},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7273690104484558},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6971426010131836},{"id":"https://openalex.org/keywords/interpretability","display_name":"Interpretability","score":0.6880958080291748},{"id":"https://openalex.org/keywords/synthetic-aperture-radar","display_name":"Synthetic aperture radar","score":0.6439522504806519},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6247913241386414},{"id":"https://openalex.org/keywords/measure","display_name":"Measure (data warehouse)","score":0.5501976609230042},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.5246185064315796},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.50592440366745},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4951101839542389},{"id":"https://openalex.org/keywords/decimation","display_name":"Decimation","score":0.4513850808143616},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.447361022233963},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.36142969131469727},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.20317605137825012},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.14696094393730164}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7496102452278137},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7273690104484558},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6971426010131836},{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.6880958080291748},{"id":"https://openalex.org/C87360688","wikidata":"https://www.wikidata.org/wiki/Q740686","display_name":"Synthetic aperture radar","level":2,"score":0.6439522504806519},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6247913241386414},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.5501976609230042},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.5246185064315796},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.50592440366745},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4951101839542389},{"id":"https://openalex.org/C173642442","wikidata":"https://www.wikidata.org/wiki/Q1253346","display_name":"Decimation","level":3,"score":0.4513850808143616},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.447361022233963},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.36142969131469727},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.20317605137825012},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.14696094393730164},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"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/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/lgrs.2023.3257412","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lgrs.2023.3257412","pdf_url":null,"source":{"id":"https://openalex.org/S126920919","display_name":"IEEE Geoscience and Remote Sensing Letters","issn_l":"1545-598X","issn":["1545-598X","1558-0571"],"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 Geoscience and Remote Sensing Letters","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G3791490203","display_name":null,"funder_award_id":"2018M633667","funder_id":"https://openalex.org/F4320321543","funder_display_name":"China Postdoctoral Science Foundation"},{"id":"https://openalex.org/G5979008009","display_name":null,"funder_award_id":"61921001","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7124874346","display_name":null,"funder_award_id":"YJKT-RC-2119","funder_id":"https://openalex.org/F4320324150","funder_display_name":"National University of Defense Technology"},{"id":"https://openalex.org/G7222141030","display_name":null,"funder_award_id":"62131030","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/F4320321543","display_name":"China Postdoctoral Science Foundation","ror":"https://ror.org/0426zh255"},{"id":"https://openalex.org/F4320324150","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W1686810756","https://openalex.org/W1722318740","https://openalex.org/W1787224781","https://openalex.org/W1982475475","https://openalex.org/W2099111195","https://openalex.org/W2194775991","https://openalex.org/W2295107390","https://openalex.org/W2410591237","https://openalex.org/W2516809705","https://openalex.org/W2762294195","https://openalex.org/W2963446712","https://openalex.org/W2964350391","https://openalex.org/W2991632793","https://openalex.org/W3035664806","https://openalex.org/W3056736931","https://openalex.org/W3169512507","https://openalex.org/W3173493671","https://openalex.org/W3201945250","https://openalex.org/W6637373629","https://openalex.org/W6684191040"],"related_works":["https://openalex.org/W2905433371","https://openalex.org/W2888392564","https://openalex.org/W4310278675","https://openalex.org/W4388422664","https://openalex.org/W4390569940","https://openalex.org/W4361193272","https://openalex.org/W2963326959","https://openalex.org/W4388685194","https://openalex.org/W4312407344","https://openalex.org/W2894289927"],"abstract_inverted_index":{"With":[0],"the":[1,21,26,29,49,59,78,86,92,95,100,107,112,116,122,137,145,154,171,176],"maturity":[2],"of":[3,31,80,94,106,115,121,153,175],"deep":[4],"learning":[5],"algorithm":[6],"in":[7,73,179],"Synthetic":[8],"Aperture":[9],"Radar":[10],"(SAR)":[11],"target":[12],"recognition":[13,151],"filed,":[14],"Convolutional":[15],"Neural":[16],"Network":[17],"(CNN)":[18],"has":[19],"become":[20],"most":[22],"effective":[23],"model.":[24,117],"However,":[25],"interpretability":[27],"and":[28,98,166,173],"separability":[30,66,93,123],"feature":[32,96],"maps":[33,97],"extracted":[34],"from":[35],"convolution":[36],"layers":[37],"have":[38],"not":[39],"been":[40],"specially":[41],"analyzed":[42],"neither":[43],"qualitatively":[44],"nor":[45],"quantitatively,":[46],"which":[47,76],"makes":[48],"traditional":[50],"model":[51,63,147],"work":[52],"like":[53],"a":[54,61,103,141],"\u201cblack":[55],"box\u201d.":[56,143],"To":[57],"alleviate":[58],"problem,":[60],"novel":[62],"based":[64,163],"on":[65,164],"measure":[67,124],"(SM)":[68],"-":[69],"CNN":[70],"is":[71,133],"proposed":[72,146,178],"this":[74,180],"letter,":[75],"introduces":[77],"principle":[79],"maximal":[81],"coding":[82],"rate":[83],"reduction":[84],"to":[85,110],"backbone":[87,155],"module.":[88],"SM-CNN":[89],"quantitatively":[90],"analyzes":[91],"takes":[99],"value":[101],"as":[102],"vital":[104],"part":[105],"loss":[108],"function":[109],"guide":[111],"training":[113],"process":[114,120],"The":[118],"calculation":[119],"values":[125],"can":[126,148],"be":[127],"strictly":[128],"derived":[129],"mathematically,":[130],"so":[131],"it":[132],"more":[134],"interpretable,":[135],"turning":[136],"black":[138],"box":[139],"into":[140],"\u201cgray":[142],"Additionally,":[144],"achieve":[149],"comparable":[150],"performance":[152],"networks":[156],"with":[157],"reduced":[158],"computational":[159],"complexity.":[160],"Comparative":[161],"experiments":[162],"MSTAR":[165],"OpenSARShip":[167],"data":[168],"sets":[169],"verify":[170],"effectiveness":[172],"practicability":[174],"method":[177],"letter.":[181]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":9},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":4}],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2025-10-10T00:00:00"}
