{"id":"https://openalex.org/W2947659462","doi":"https://doi.org/10.1109/qomex.2019.8743213","title":"Perceptual Evaluation of Adversarial Attacks for CNN-based Image Classification","display_name":"Perceptual Evaluation of Adversarial Attacks for CNN-based Image Classification","publication_year":2019,"publication_date":"2019-06-01","ids":{"openalex":"https://openalex.org/W2947659462","doi":"https://doi.org/10.1109/qomex.2019.8743213","mag":"2947659462"},"language":"en","primary_location":{"id":"doi:10.1109/qomex.2019.8743213","is_oa":false,"landing_page_url":"https://doi.org/10.1109/qomex.2019.8743213","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 Eleventh International Conference on Quality of Multimedia Experience (QoMEX)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1906.00204","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5055759473","display_name":"Sid Ahmed Fezza","orcid":"https://orcid.org/0000-0001-6453-8588"},"institutions":[{"id":"https://openalex.org/I4210116811","display_name":"Ecole Nationale Sup\u00e9rieur des T\u00e9l\u00e9communications et des Technologies de l\u2019Information et de la Communication, Abdelhafid Boussouf","ror":"https://ror.org/023rzn231","country_code":"DZ","type":"education","lineage":["https://openalex.org/I4210116811"]}],"countries":["DZ"],"is_corresponding":false,"raw_author_name":"Sid Ahmed Fezza","raw_affiliation_strings":["National Institute of Telecommunications and ICT, Oran, Algeria"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Institute of Telecommunications and ICT, Oran, Algeria","institution_ids":["https://openalex.org/I4210116811"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5017368218","display_name":"Yassine Bakhti","orcid":"https://orcid.org/0000-0002-0502-8841"},"institutions":[{"id":"https://openalex.org/I4210116811","display_name":"Ecole Nationale Sup\u00e9rieur des T\u00e9l\u00e9communications et des Technologies de l\u2019Information et de la Communication, Abdelhafid Boussouf","ror":"https://ror.org/023rzn231","country_code":"DZ","type":"education","lineage":["https://openalex.org/I4210116811"]}],"countries":["DZ"],"is_corresponding":false,"raw_author_name":"Yassine Bakhti","raw_affiliation_strings":["National Institute of Telecommunications and ICT, Oran, Algeria"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Institute of Telecommunications and ICT, Oran, Algeria","institution_ids":["https://openalex.org/I4210116811"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5084205574","display_name":"Wassim Hamidouche","orcid":"https://orcid.org/0000-0002-0143-1756"},"institutions":[{"id":"https://openalex.org/I1294671590","display_name":"Centre National de la Recherche Scientifique","ror":"https://ror.org/02feahw73","country_code":"FR","type":"government","lineage":["https://openalex.org/I1294671590"]},{"id":"https://openalex.org/I28221208","display_name":"Institut National des Sciences Appliqu\u00e9es de Rennes","ror":"https://ror.org/04xaa4j22","country_code":"FR","type":"education","lineage":["https://openalex.org/I28221208"]},{"id":"https://openalex.org/I56067802","display_name":"Universit\u00e9 de Rennes","ror":"https://ror.org/015m7wh34","country_code":"FR","type":"education","lineage":["https://openalex.org/I56067802"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Wassim Hamidouche","raw_affiliation_strings":["INSA Rennes, CNRS, Univ. Rennes, Rennes, France"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"INSA Rennes, CNRS, Univ. Rennes, Rennes, France","institution_ids":["https://openalex.org/I1294671590","https://openalex.org/I28221208","https://openalex.org/I56067802"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5031377954","display_name":"Olivier D\u00e9forges","orcid":"https://orcid.org/0000-0003-0750-0959"},"institutions":[{"id":"https://openalex.org/I1294671590","display_name":"Centre National de la Recherche Scientifique","ror":"https://ror.org/02feahw73","country_code":"FR","type":"government","lineage":["https://openalex.org/I1294671590"]},{"id":"https://openalex.org/I28221208","display_name":"Institut National des Sciences Appliqu\u00e9es de Rennes","ror":"https://ror.org/04xaa4j22","country_code":"FR","type":"education","lineage":["https://openalex.org/I28221208"]},{"id":"https://openalex.org/I56067802","display_name":"Universit\u00e9 de Rennes","ror":"https://ror.org/015m7wh34","country_code":"FR","type":"education","lineage":["https://openalex.org/I56067802"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Olivier Deforges","raw_affiliation_strings":["INSA Rennes, CNRS, Univ. Rennes, Rennes, France"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"INSA Rennes, CNRS, Univ. Rennes, Rennes, France","institution_ids":["https://openalex.org/I1294671590","https://openalex.org/I28221208","https://openalex.org/I56067802"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":3,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9998999834060669,"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":0.9998999834060669,"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":0.9930999875068665,"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/T14117","display_name":"Integrated Circuits and Semiconductor Failure Analysis","score":0.9854000210762024,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic 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/adversarial-system","display_name":"Adversarial system","score":0.8740248680114746},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7244554758071899},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.6806957721710205},{"id":"https://openalex.org/keywords/fidelity","display_name":"Fidelity","score":0.6738249659538269},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6079016327857971},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.5612939596176147},{"id":"https://openalex.org/keywords/perception","display_name":"Perception","score":0.5465190410614014},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.4664119482040405},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4296831488609314},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.4242454171180725},{"id":"https://openalex.org/keywords/deep-neural-networks","display_name":"Deep neural networks","score":0.42050546407699585},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4062490165233612},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.329484224319458},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.13637423515319824},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.07971227169036865}],"concepts":[{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.8740248680114746},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7244554758071899},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.6806957721710205},{"id":"https://openalex.org/C2776459999","wikidata":"https://www.wikidata.org/wiki/Q2119376","display_name":"Fidelity","level":2,"score":0.6738249659538269},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6079016327857971},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.5612939596176147},{"id":"https://openalex.org/C26760741","wikidata":"https://www.wikidata.org/wiki/Q160402","display_name":"Perception","level":2,"score":0.5465190410614014},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.4664119482040405},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4296831488609314},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.4242454171180725},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.42050546407699585},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4062490165233612},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.329484224319458},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.13637423515319824},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.07971227169036865},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C169760540","wikidata":"https://www.wikidata.org/wiki/Q207011","display_name":"Neuroscience","level":1,"score":0.0}],"mesh":[],"locations_count":5,"locations":[{"id":"doi:10.1109/qomex.2019.8743213","is_oa":false,"landing_page_url":"https://doi.org/10.1109/qomex.2019.8743213","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 Eleventh International Conference on Quality of Multimedia Experience (QoMEX)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:1906.00204","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1906.00204","pdf_url":"https://arxiv.org/pdf/1906.00204","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"pmh:oai:HAL:hal-02302604v1","is_oa":false,"landing_page_url":"https://univ-rennes.hal.science/hal-02302604","pdf_url":null,"source":{"id":"https://openalex.org/S4306402512","display_name":"HAL (Le Centre pour la Communication Scientifique Directe)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1294671590","host_organization_name":"Centre National de la Recherche Scientifique","host_organization_lineage":["https://openalex.org/I1294671590"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"11th International Conference on Quality of Multimedia Experience (QoMEX), Jun 2019, Berlin, Germany","raw_type":"info:eu-repo/semantics/conferenceObject"},{"id":"pmh:oai:HAL:hal-02304389v1","is_oa":false,"landing_page_url":"https://hal-univ-rennes1.archives-ouvertes.fr/hal-02304389","pdf_url":null,"source":{"id":"https://openalex.org/S4306402512","display_name":"HAL (Le Centre pour la Communication Scientifique Directe)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1294671590","host_organization_name":"Centre National de la Recherche Scientifique","host_organization_lineage":["https://openalex.org/I1294671590"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"2019 Eleventh International Conference on Quality of Multimedia Experience (QoMEX)","raw_type":"info:eu-repo/semantics/conferenceObject"},{"id":"doi:10.48550/arxiv.1906.00204","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.1906.00204","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1906.00204","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1906.00204","pdf_url":"https://arxiv.org/pdf/1906.00204","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[{"display_name":"Quality Education","score":0.6000000238418579,"id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2947659462.pdf","grobid_xml":"https://content.openalex.org/works/W2947659462.grobid-xml"},"referenced_works_count":41,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W1580389772","https://openalex.org/W1673923490","https://openalex.org/W1972006393","https://openalex.org/W1973207880","https://openalex.org/W2009272644","https://openalex.org/W2015196405","https://openalex.org/W2046119925","https://openalex.org/W2108657140","https://openalex.org/W2117539524","https://openalex.org/W2130942839","https://openalex.org/W2132549992","https://openalex.org/W2133665775","https://openalex.org/W2141983208","https://openalex.org/W2142884912","https://openalex.org/W2144468361","https://openalex.org/W2159269332","https://openalex.org/W2160815625","https://openalex.org/W2161304138","https://openalex.org/W2161907179","https://openalex.org/W2163605009","https://openalex.org/W2171349048","https://openalex.org/W2183341477","https://openalex.org/W2243397390","https://openalex.org/W2245625259","https://openalex.org/W2613718673","https://openalex.org/W2626610348","https://openalex.org/W2774644650","https://openalex.org/W2962700793","https://openalex.org/W2963178695","https://openalex.org/W2963207607","https://openalex.org/W2963542245","https://openalex.org/W2963857521","https://openalex.org/W2964253222","https://openalex.org/W6637162671","https://openalex.org/W6640425456","https://openalex.org/W6679436768","https://openalex.org/W6684191040","https://openalex.org/W6719080892","https://openalex.org/W6739868092","https://openalex.org/W6747220948"],"related_works":["https://openalex.org/W2955127209","https://openalex.org/W2901503903","https://openalex.org/W3013884416","https://openalex.org/W3001281326","https://openalex.org/W3199178087","https://openalex.org/W3175085978","https://openalex.org/W2997645422","https://openalex.org/W2755252132","https://openalex.org/W3135626921","https://openalex.org/W2949152835","https://openalex.org/W3107156893","https://openalex.org/W2965595599","https://openalex.org/W2971970905","https://openalex.org/W3011041688","https://openalex.org/W2967398859","https://openalex.org/W3017885892","https://openalex.org/W2916168812","https://openalex.org/W3036238396","https://openalex.org/W2995592330","https://openalex.org/W3175274127"],"abstract_inverted_index":{"Deep":[0],"neural":[1],"networks":[2],"(DNNs)":[3],"have":[4,31,94],"recently":[5],"achieved":[6],"state-of-the-art":[7,165],"performance":[8,162],"and":[9,61,112,159,194],"provide":[10],"significant":[11],"progress":[12],"in":[13,42,87],"many":[14],"machine":[15],"learning":[16],"tasks,":[17],"such":[18],"as":[19,74,76,101,178,180],"image":[20,44,54,111,168],"classification,":[21],"speech":[22],"processing,":[23,26],"natural":[24],"language":[25],"etc.":[27],"However,":[28,82],"recent":[29],"studies":[30],"shown":[32],"that":[33,172],"DNNs":[34],"are":[35,183],"vulnerable":[36],"to":[37,51,57,62,78,104,129,186,195],"adversarial":[38,69,92,114,136,150,192],"attacks.":[39],"For":[40],"instance,":[41],"the":[43,52,59,79,84,88,96,106,109,113,117,132,154,157,161],"classification":[45],"domain,":[46],"adding":[47],"small":[48],"imperceptible":[49],"perturbations":[50],"input":[53],"is":[55],"sufficient":[56],"fool":[58],"DNN":[60],"cause":[63],"misclassification.":[64],"The":[65,176],"perturbed":[66],"image,":[67],"called":[68],"example,":[70],"should":[71],"be":[72],"visually":[73],"close":[75],"possible":[77],"original":[80,110],"image.":[81],"all":[83],"works":[85],"proposed":[86],"literature":[89],"for":[90,145,191],"generating":[91],"examples":[93,193],"used":[95],"Lpnorms":[97,118],"(L0,":[98],"L2and":[99],"L\u221e)":[100],"distance":[102],"metrics":[103,171,190],"quantify":[105],"similarity":[107],"between":[108],"example.":[115],"Nonetheless,":[116],"do":[119],"not":[120,127],"correlate":[121],"with":[122],"human":[123],"judgment,":[124],"making":[125],"them":[126],"suitable":[128],"reliably":[130],"assess":[131],"perceptual":[133],"similarity/fidelity":[134],"of":[135,149,156,163],"examples.":[137,151],"In":[138],"this":[139],"paper,":[140],"we":[141],"present":[142],"a":[143],"database":[144,158,177],"visual":[146],"fidelity":[147,169],"assessment":[148,170],"We":[152],"describe":[153],"creation":[155],"evaluate":[160],"fifteen":[164],"full-reference":[166],"(FR)":[167],"could":[173],"substitute":[174],"Lpnorms.":[175],"well":[179],"subjective":[181],"scores":[182],"publicly":[184],"available":[185],"help":[187],"designing":[188],"new":[189],"facilitate":[196],"future":[197],"research":[198],"works.":[199]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1}],"updated_date":"2026-07-29T09:40:50.615796","created_date":"2025-10-10T00:00:00"}
