{"id":"https://openalex.org/W4402261306","doi":"https://doi.org/10.1109/igarss53475.2024.10641464","title":"Adversarial Robustness of Deep Learning Methods for SAR Image Classification: An Explainability View","display_name":"Adversarial Robustness of Deep Learning Methods for SAR Image Classification: An Explainability View","publication_year":2024,"publication_date":"2024-07-07","ids":{"openalex":"https://openalex.org/W4402261306","doi":"https://doi.org/10.1109/igarss53475.2024.10641464"},"language":"en","primary_location":{"id":"doi:10.1109/igarss53475.2024.10641464","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss53475.2024.10641464","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/A5101581575","display_name":"Tianrui Chen","orcid":"https://orcid.org/0000-0002-4694-5267"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tianrui Chen","raw_affiliation_strings":["Shanghai Jiao Tong University,Shanghai Key Lab. of Intelligent Sensing and Recognition,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University,Shanghai Key Lab. of Intelligent Sensing and Recognition,China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5017760080","display_name":"Juanping Wu","orcid":"https://orcid.org/0000-0001-6395-4336"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Juanping Wu","raw_affiliation_strings":["Shanghai Jiao Tong University,Shanghai Key Lab. of Intelligent Sensing and Recognition,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University,Shanghai Key Lab. of Intelligent Sensing and Recognition,China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5027639981","display_name":"Weiwei Guo","orcid":"https://orcid.org/0000-0001-5037-0972"},"institutions":[{"id":"https://openalex.org/I116953780","display_name":"Tongji University","ror":"https://ror.org/03rc6as71","country_code":"CN","type":"education","lineage":["https://openalex.org/I116953780"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weiwei Guo","raw_affiliation_strings":["Tongji University,Center of Digital Innovation,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tongji University,Center of Digital Innovation,China","institution_ids":["https://openalex.org/I116953780"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5059094652","display_name":"Zenghui Zhang","orcid":"https://orcid.org/0000-0002-1238-8538"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zenghui Zhang","raw_affiliation_strings":["Shanghai Jiao Tong University,Shanghai Key Lab. of Intelligent Sensing and Recognition,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University,Shanghai Key Lab. of Intelligent Sensing and Recognition,China","institution_ids":["https://openalex.org/I183067930"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"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":"1987","last_page":"1991"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9994000196456909,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9994000196456909,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.989300012588501,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.9821000099182129,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.8100001811981201},{"id":"https://openalex.org/keywords/adversarial-system","display_name":"Adversarial system","score":0.7733365893363953},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7217713594436646},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6913188695907593},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5530579090118408},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.5450360178947449},{"id":"https://openalex.org/keywords/synthetic-aperture-radar","display_name":"Synthetic aperture radar","score":0.5244362950325012},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5091907382011414},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4281252920627594},{"id":"https://openalex.org/keywords/radar-imaging","display_name":"Radar imaging","score":0.41761264204978943},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.3491027057170868},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3416929841041565},{"id":"https://openalex.org/keywords/radar","display_name":"Radar","score":0.14680248498916626},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.0683535635471344}],"concepts":[{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.8100001811981201},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.7733365893363953},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7217713594436646},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6913188695907593},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5530579090118408},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.5450360178947449},{"id":"https://openalex.org/C87360688","wikidata":"https://www.wikidata.org/wiki/Q740686","display_name":"Synthetic aperture radar","level":2,"score":0.5244362950325012},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5091907382011414},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4281252920627594},{"id":"https://openalex.org/C10929652","wikidata":"https://www.wikidata.org/wiki/Q7279985","display_name":"Radar imaging","level":3,"score":0.41761264204978943},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3491027057170868},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3416929841041565},{"id":"https://openalex.org/C554190296","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar","level":2,"score":0.14680248498916626},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0683535635471344},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/igarss53475.2024.10641464","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss53475.2024.10641464","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"},{"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":27,"referenced_works":["https://openalex.org/W1945616565","https://openalex.org/W2010853190","https://openalex.org/W2194775991","https://openalex.org/W2410591237","https://openalex.org/W2560662850","https://openalex.org/W2762294195","https://openalex.org/W2775716424","https://openalex.org/W2809671526","https://openalex.org/W2810611310","https://openalex.org/W2913668833","https://openalex.org/W2951885001","https://openalex.org/W2971201880","https://openalex.org/W3085380432","https://openalex.org/W3211012720","https://openalex.org/W4293846201","https://openalex.org/W4312996414","https://openalex.org/W4391933803","https://openalex.org/W6637162671","https://openalex.org/W6637373629","https://openalex.org/W6640425456","https://openalex.org/W6734194636","https://openalex.org/W6736518430","https://openalex.org/W6739575509","https://openalex.org/W6752170072","https://openalex.org/W6752931940","https://openalex.org/W6762929394","https://openalex.org/W6783213970"],"related_works":["https://openalex.org/W2545123933","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","https://openalex.org/W1908997176"],"abstract_inverted_index":{"The":[0,124],"application":[1],"of":[2,23,38,92,134],"deep":[3,39,47],"learning":[4,40],"in":[5,55,118,137],"the":[6,21,34,90,101,131],"synthetic":[7],"aperture":[8],"radar":[9],"(SAR)":[10],"field":[11],"is":[12],"becoming":[13],"increasingly":[14],"widespread,":[15],"but":[16],"its":[17,27],"black-box":[18],"nature":[19],"and":[20,36,69,99,111],"existence":[22],"adversarial":[24,72,132],"samples":[25],"limit":[26],"practical":[28],"utility.":[29],"In":[30],"order":[31],"to":[32,65,75,88,108],"enhance":[33],"explainability":[35,143],"security":[37],"models,":[41,68],"we":[42,60,80],"initially":[43],"selected":[44],"3":[45,82],"different":[46,93,97],"convolutional":[48],"neural":[49],"network":[50],"(DCNN)":[51],"structures":[52],"for":[53],"training":[54],"SAR":[56,138],"image":[57,139],"classification.":[58],"Subsequently,":[59],"applied":[61],"Madry":[62,102],"Defense":[63,103],"Method":[64,104],"obtain":[66],"robust":[67],"used":[70],"2":[71],"attack":[73,76],"methods":[74,87],"DCNN":[77,94,135],"classifiers.":[78,95],"Finally,":[79],"employed":[81],"explainable":[83],"artificial":[84],"intelligence":[85],"(XAI)":[86],"explain":[89],"predictions":[91],"Across":[96],"datasets":[98],"DCNNs,":[100],"helps":[105],"classification":[106,140],"models":[107],"reduce":[109],"Infidelity":[110],"focus":[112],"more":[113],"on":[114],"feature":[115],"regions":[116],"rich":[117],"semantic":[119],"information":[120],"when":[121],"making":[122],"decisions.":[123],"experimental":[125],"results":[126],"provide":[127],"new":[128],"insights":[129],"into":[130],"robustness":[133],"classifiers":[136],"from":[141],"an":[142],"viewpoint.":[144]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}