{"id":"https://openalex.org/W4290996763","doi":"https://doi.org/10.1109/icc45855.2022.9838630","title":"A Heterogeneous Feature Ensemble Learning based Deepfake Detection Method","display_name":"A Heterogeneous Feature Ensemble Learning based Deepfake Detection Method","publication_year":2022,"publication_date":"2022-05-16","ids":{"openalex":"https://openalex.org/W4290996763","doi":"https://doi.org/10.1109/icc45855.2022.9838630"},"language":"en","primary_location":{"id":"doi:10.1109/icc45855.2022.9838630","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icc45855.2022.9838630","pdf_url":null,"source":{"id":"https://openalex.org/S4363607711","display_name":"ICC 2022 - IEEE International Conference on Communications","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICC 2022 - IEEE International Conference on Communications","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/A5081463234","display_name":"Jixin Zhang","orcid":"https://orcid.org/0000-0001-6890-8953"},"institutions":[{"id":"https://openalex.org/I74525822","display_name":"Hubei University of Technology","ror":"https://ror.org/02d3fj342","country_code":"CN","type":"education","lineage":["https://openalex.org/I74525822"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jixin Zhang","raw_affiliation_strings":["Hubei University of Technology,School of Computer Science,China","School of Computer Science, Hubei University of Technology, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Hubei University of Technology,School of Computer Science,China","institution_ids":["https://openalex.org/I74525822"]},{"raw_affiliation_string":"School of Computer Science, Hubei University of Technology, China","institution_ids":["https://openalex.org/I74525822"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5011609454","display_name":"Ke Cheng","orcid":"https://orcid.org/0000-0002-5081-9247"},"institutions":[{"id":"https://openalex.org/I74525822","display_name":"Hubei University of Technology","ror":"https://ror.org/02d3fj342","country_code":"CN","type":"education","lineage":["https://openalex.org/I74525822"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ke Cheng","raw_affiliation_strings":["Hubei University of Technology,School of Computer Science,China","School of Computer Science, Hubei University of Technology, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Hubei University of Technology,School of Computer Science,China","institution_ids":["https://openalex.org/I74525822"]},{"raw_affiliation_string":"School of Computer Science, Hubei University of Technology, China","institution_ids":["https://openalex.org/I74525822"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5028325209","display_name":"Giuliano Sovernigo","orcid":null},"institutions":[{"id":"https://openalex.org/I79817857","display_name":"University of Guelph","ror":"https://ror.org/01r7awg59","country_code":"CA","type":"education","lineage":["https://openalex.org/I79817857"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Giuliano Sovernigo","raw_affiliation_strings":["University of Guelph,School of Computer Science,Canada","School of Computer Science, University of Guelph, Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Guelph,School of Computer Science,Canada","institution_ids":["https://openalex.org/I79817857"]},{"raw_affiliation_string":"School of Computer Science, University of Guelph, Canada","institution_ids":["https://openalex.org/I79817857"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5083787204","display_name":"Xiaodong Lin","orcid":"https://orcid.org/0000-0001-8916-6645"},"institutions":[{"id":"https://openalex.org/I79817857","display_name":"University of Guelph","ror":"https://ror.org/01r7awg59","country_code":"CA","type":"education","lineage":["https://openalex.org/I79817857"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Xiaodong Lin","raw_affiliation_strings":["University of Guelph,School of Computer Science,Canada","School of Computer Science, University of Guelph, Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Guelph,School of Computer Science,Canada","institution_ids":["https://openalex.org/I79817857"]},{"raw_affiliation_string":"School of Computer Science, University of Guelph, Canada","institution_ids":["https://openalex.org/I79817857"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":24,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"2084","last_page":"2089"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12357","display_name":"Digital Media Forensic Detection","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T12357","display_name":"Digital Media Forensic Detection","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.9995999932289124,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T11105","display_name":"Advanced Image Processing Techniques","score":0.9904999732971191,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/computer-science","display_name":"Computer science","score":0.8131896257400513},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7407068014144897},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6001192331314087},{"id":"https://openalex.org/keywords/swap","display_name":"Swap (finance)","score":0.5755717158317566},{"id":"https://openalex.org/keywords/face","display_name":"Face (sociological concept)","score":0.5427629351615906},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5376670360565186},{"id":"https://openalex.org/keywords/feature-vector","display_name":"Feature vector","score":0.5274695754051208},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.46779733896255493},{"id":"https://openalex.org/keywords/detector","display_name":"Detector","score":0.4554538130760193},{"id":"https://openalex.org/keywords/ensemble-learning","display_name":"Ensemble learning","score":0.4492085874080658},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.4379371404647827},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.39729517698287964},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.34241241216659546}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8131896257400513},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7407068014144897},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6001192331314087},{"id":"https://openalex.org/C99821215","wikidata":"https://www.wikidata.org/wiki/Q1136583","display_name":"Swap (finance)","level":2,"score":0.5755717158317566},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.5427629351615906},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5376670360565186},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.5274695754051208},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.46779733896255493},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.4554538130760193},{"id":"https://openalex.org/C45942800","wikidata":"https://www.wikidata.org/wiki/Q245652","display_name":"Ensemble learning","level":2,"score":0.4492085874080658},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.4379371404647827},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.39729517698287964},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.34241241216659546},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C10138342","wikidata":"https://www.wikidata.org/wiki/Q43015","display_name":"Finance","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"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/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C36289849","wikidata":"https://www.wikidata.org/wiki/Q34749","display_name":"Social science","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icc45855.2022.9838630","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icc45855.2022.9838630","pdf_url":null,"source":{"id":"https://openalex.org/S4363607711","display_name":"ICC 2022 - IEEE International Conference on Communications","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICC 2022 - IEEE International Conference on Communications","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.800000011920929,"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320321604","display_name":"Hubei University of Technology","ror":"https://ror.org/02d3fj342"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W2486034530","https://openalex.org/W2521028896","https://openalex.org/W2804078698","https://openalex.org/W2945262873","https://openalex.org/W2962770929","https://openalex.org/W2962793481","https://openalex.org/W2963684088","https://openalex.org/W2963767194","https://openalex.org/W3010699567","https://openalex.org/W3034577585","https://openalex.org/W3034864980","https://openalex.org/W3036806226","https://openalex.org/W3038930935","https://openalex.org/W4294643831","https://openalex.org/W4295274059","https://openalex.org/W6685352114","https://openalex.org/W6727501944","https://openalex.org/W6736155344","https://openalex.org/W6745560452","https://openalex.org/W6752378368","https://openalex.org/W6762480454"],"related_works":["https://openalex.org/W614339039","https://openalex.org/W3124943098","https://openalex.org/W4308112567","https://openalex.org/W3162132941","https://openalex.org/W3048601286","https://openalex.org/W2965925734","https://openalex.org/W2786094008","https://openalex.org/W3131501806","https://openalex.org/W2799683370","https://openalex.org/W2807745940"],"abstract_inverted_index":{"The":[0],"Deepfake":[1],"technique":[2],"can":[3],"swap":[4],"the":[5,11,118],"face":[6,12,91],"of":[7,13],"a":[8,20,25,102,108,114],"person":[9,15],"with":[10,117,132],"another":[14],"in":[16],"an":[17,97],"image":[18],"or":[19],"video":[21],"which":[22],"may":[23],"cause":[24],"public":[26],"security":[27],"problem.":[28],"Recently,":[29],"researchers":[30],"have":[31,44],"focused":[32],"on":[33,49,60],"detecting":[34],"deepfake":[35,54,69,115,135],"images":[36,50,70],"by":[37,52],"deep":[38],"learning.":[39,75],"However":[40],"some":[41],"recent":[42],"works":[43],"observed":[45],"that":[46,124],"detectors":[47],"trained":[48],"produced":[51],"one":[53],"model":[55],"perform":[56],"poorly":[57],"when":[58],"tested":[59],"others.":[61],"In":[62],"this":[63],"paper":[64],"we":[65],"propose":[66],"to":[67,112],"detect":[68],"through":[71,101],"heterogeneous":[72],"feature":[73,99,119],"ensemble":[74,98],"We":[76],"first":[77],"extract":[78],"gray":[79],"gradient":[80],"features,":[81],"spectrum":[82],"features":[83,86],"and":[84,89,105],"texture":[85],"from":[87],"real":[88],"fake":[90],"images,":[92],"then":[93],"integrate":[94],"them":[95],"into":[96],"vector":[100],"flatten":[103],"process,":[104],"finally":[106],"adopt":[107],"back-propagation":[109],"neural":[110],"network":[111],"train":[113],"detector":[116],"vector.":[120],"Experimental":[121],"results":[122],"show":[123],"our":[125],"approach":[126],"achieves":[127],"better":[128],"detection":[129],"accuracy":[130],"compared":[131],"several":[133],"state-of-the-art":[134],"detectors.":[136]},"counts_by_year":[{"year":2026,"cited_by_count":7},{"year":2025,"cited_by_count":11},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
