{"id":"https://openalex.org/W4206593088","doi":"https://doi.org/10.3390/e24010118","title":"MFAN: Multi-Level Features Attention Network for Fake Certificate Image Detection","display_name":"MFAN: Multi-Level Features Attention Network for Fake Certificate Image Detection","publication_year":2022,"publication_date":"2022-01-13","ids":{"openalex":"https://openalex.org/W4206593088","doi":"https://doi.org/10.3390/e24010118","pmid":"https://pubmed.ncbi.nlm.nih.gov/35052144"},"language":"en","primary_location":{"id":"doi:10.3390/e24010118","is_oa":true,"landing_page_url":"https://doi.org/10.3390/e24010118","pdf_url":"https://www.mdpi.com/1099-4300/24/1/118/pdf?version=1642058807","source":{"id":"https://openalex.org/S195231649","display_name":"Entropy","issn_l":"1099-4300","issn":["1099-4300"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Entropy","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/1099-4300/24/1/118/pdf?version=1642058807","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5066377083","display_name":"Yu Sun","orcid":"https://orcid.org/0000-0002-9348-6112"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yu Sun","raw_affiliation_strings":["Beijing Key Laboratory of Advanced Information Science and Network Technology, Beijing Jiaotong University, Beijing 100044, China","Institute of Information Science, Beijing Jiaotong University, Beijing 100044, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing Key Laboratory of Advanced Information Science and Network Technology, Beijing Jiaotong University, Beijing 100044, China","institution_ids":["https://openalex.org/I21193070"]},{"raw_affiliation_string":"Institute of Information Science, Beijing Jiaotong University, Beijing 100044, China","institution_ids":["https://openalex.org/I21193070"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5007154515","display_name":"Rongrong Ni","orcid":"https://orcid.org/0000-0002-5096-8752"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Rongrong Ni","raw_affiliation_strings":["Beijing Key Laboratory of Advanced Information Science and Network Technology, Beijing Jiaotong University, Beijing 100044, China","Institute of Information Science, Beijing Jiaotong University, Beijing 100044, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing Key Laboratory of Advanced Information Science and Network Technology, Beijing Jiaotong University, Beijing 100044, China","institution_ids":["https://openalex.org/I21193070"]},{"raw_affiliation_string":"Institute of Information Science, Beijing Jiaotong University, Beijing 100044, China","institution_ids":["https://openalex.org/I21193070"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100362745","display_name":"Yao Zhao","orcid":"https://orcid.org/0000-0002-8581-9554"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yao Zhao","raw_affiliation_strings":["Beijing Key Laboratory of Advanced Information Science and Network Technology, Beijing Jiaotong University, Beijing 100044, China","Institute of Information Science, Beijing Jiaotong University, Beijing 100044, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing Key Laboratory of Advanced Information Science and Network Technology, Beijing Jiaotong University, Beijing 100044, China","institution_ids":["https://openalex.org/I21193070"]},{"raw_affiliation_string":"Institute of Information Science, Beijing Jiaotong University, Beijing 100044, China","institution_ids":["https://openalex.org/I21193070"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5007154515"],"corresponding_institution_ids":["https://openalex.org/I21193070"],"apc_list":{"value":2000,"currency":"CHF","value_usd":2227},"apc_paid":{"value":2000,"currency":"CHF","value_usd":2227},"fwci":1.0528,"has_fulltext":false,"cited_by_count":15,"citation_normalized_percentile":{"value":0.75027922,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":98},"biblio":{"volume":"24","issue":"1","first_page":"118","last_page":"118"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12357","display_name":"Digital Media Forensic Detection","score":1.0,"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":1.0,"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/T10388","display_name":"Advanced Steganography and Watermarking Techniques","score":0.9805999994277954,"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/T13877","display_name":"Law in Society and Culture","score":0.9621999859809875,"subfield":{"id":"https://openalex.org/subfields/3308","display_name":"Law"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8401587009429932},{"id":"https://openalex.org/keywords/pyramid","display_name":"Pyramid (geometry)","score":0.6728904843330383},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6045151948928833},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5611140727996826},{"id":"https://openalex.org/keywords/pooling","display_name":"Pooling","score":0.5228329300880432},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.5190325975418091},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.48605969548225403},{"id":"https://openalex.org/keywords/certificate","display_name":"Certificate","score":0.45414140820503235},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.43424317240715027},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.42662158608436584},{"id":"https://openalex.org/keywords/attention-network","display_name":"Attention network","score":0.4133238196372986},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.41318461298942566},{"id":"https://openalex.org/keywords/residual","display_name":"Residual","score":0.41202571988105774},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3431815803050995},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.07495629787445068}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8401587009429932},{"id":"https://openalex.org/C142575187","wikidata":"https://www.wikidata.org/wiki/Q3358290","display_name":"Pyramid (geometry)","level":2,"score":0.6728904843330383},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6045151948928833},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5611140727996826},{"id":"https://openalex.org/C70437156","wikidata":"https://www.wikidata.org/wiki/Q7228652","display_name":"Pooling","level":2,"score":0.5228329300880432},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.5190325975418091},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.48605969548225403},{"id":"https://openalex.org/C96865113","wikidata":"https://www.wikidata.org/wiki/Q2946816","display_name":"Certificate","level":2,"score":0.45414140820503235},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.43424317240715027},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.42662158608436584},{"id":"https://openalex.org/C2993807640","wikidata":"https://www.wikidata.org/wiki/Q103709453","display_name":"Attention network","level":2,"score":0.4133238196372986},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.41318461298942566},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.41202571988105774},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3431815803050995},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.07495629787445068},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":5,"locations":[{"id":"doi:10.3390/e24010118","is_oa":true,"landing_page_url":"https://doi.org/10.3390/e24010118","pdf_url":"https://www.mdpi.com/1099-4300/24/1/118/pdf?version=1642058807","source":{"id":"https://openalex.org/S195231649","display_name":"Entropy","issn_l":"1099-4300","issn":["1099-4300"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Entropy","raw_type":"journal-article"},{"id":"pmid:35052144","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/35052144","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Entropy (Basel, Switzerland)","raw_type":null},{"id":"pmh:oai:doaj.org/article:144102ea8d3048b78c88bd69f3576a88","is_oa":true,"landing_page_url":"https://doaj.org/article/144102ea8d3048b78c88bd69f3576a88","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","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":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Entropy, Vol 24, Iss 1, p 118 (2022)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/1099-4300/24/1/118/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/e24010118","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Entropy; Volume 24; Issue 1; Pages: 118","raw_type":"Text"},{"id":"pmh:oai:pubmedcentral.nih.gov:8774785","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/8774785","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Entropy (Basel)","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/e24010118","is_oa":true,"landing_page_url":"https://doi.org/10.3390/e24010118","pdf_url":"https://www.mdpi.com/1099-4300/24/1/118/pdf?version=1642058807","source":{"id":"https://openalex.org/S195231649","display_name":"Entropy","issn_l":"1099-4300","issn":["1099-4300"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Entropy","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","score":0.800000011920929,"display_name":"Peace, Justice and strong institutions"}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4206593088.pdf"},"referenced_works_count":42,"referenced_works":["https://openalex.org/W2014400824","https://openalex.org/W2035432621","https://openalex.org/W2041625490","https://openalex.org/W2071794886","https://openalex.org/W2071869680","https://openalex.org/W2087361987","https://openalex.org/W2104116677","https://openalex.org/W2162963619","https://openalex.org/W2407845667","https://openalex.org/W2621311857","https://openalex.org/W2625745508","https://openalex.org/W2733670919","https://openalex.org/W2752782242","https://openalex.org/W2754376709","https://openalex.org/W2787655010","https://openalex.org/W2794770466","https://openalex.org/W2798117183","https://openalex.org/W2801560392","https://openalex.org/W2802173845","https://openalex.org/W2802701183","https://openalex.org/W2808402081","https://openalex.org/W2888519208","https://openalex.org/W2895129173","https://openalex.org/W2897180259","https://openalex.org/W2905384029","https://openalex.org/W2915854594","https://openalex.org/W2931259866","https://openalex.org/W2948407537","https://openalex.org/W2963727650","https://openalex.org/W2964146055","https://openalex.org/W2965545961","https://openalex.org/W3000028563","https://openalex.org/W3005497689","https://openalex.org/W3008227768","https://openalex.org/W3034779438","https://openalex.org/W3046544926","https://openalex.org/W3116585919","https://openalex.org/W3129315061","https://openalex.org/W3135925326","https://openalex.org/W3138202081","https://openalex.org/W3154575015","https://openalex.org/W6781212736"],"related_works":["https://openalex.org/W2022849497","https://openalex.org/W2407190427","https://openalex.org/W3081299480","https://openalex.org/W2919210741","https://openalex.org/W2907584218","https://openalex.org/W3002446410","https://openalex.org/W4390224712","https://openalex.org/W4322096758","https://openalex.org/W3161582628","https://openalex.org/W2937120648"],"abstract_inverted_index":{"Up":[0],"to":[1,12,83,113,129,133,157,159,175],"now,":[2],"most":[3],"of":[4,20,108],"the":[5,18,77,91,94,105,115,122,131,137,151,155,164,167,178,185],"forensics":[6,22,191],"methods":[7],"have":[8],"attached":[9],"more":[10],"attention":[11],"natural":[13],"content":[14],"images.":[15,57],"To":[16,58],"expand":[17],"application":[19],"image":[21],"technology,":[23],"forgery":[24],"detection":[25],"for":[26,145],"certificate":[27,56],"images":[28],"that":[29,184],"can":[30],"directly":[31],"represent":[32],"people's":[33],"rights":[34],"and":[35,46,149,173],"interests":[36],"is":[37,71,74],"investigated":[38],"in":[39,54,90],"this":[40,60],"paper.":[41],"Variable":[42],"tampered":[43,152],"region":[44],"scales":[45],"diverse":[47,160],"manipulation":[48,161],"types":[49],"are":[50,127,141,171],"two":[51],"typical":[52],"characteristics":[53],"fake":[55],"tackle":[59],"task,":[61],"a":[62,109],"novel":[63],"method":[64,187],"called":[65],"Multi-level":[66],"Feature":[67],"Attention":[68],"Network":[69],"(MFAN)":[70],"proposed.":[72],"MFAN":[73,156],"built":[75],"following":[76],"encoder-decoder":[78],"network":[79,112],"structure.":[80],"In":[81,163],"order":[82],"extract":[84],"features":[85,126,140],"with":[86],"rich":[87],"scale":[88],"information":[89,117,147],"encoder,":[92],"on":[93,104,121,143],"one":[95],"hand,":[96,124],"we":[97],"employ":[98],"Atrous":[99],"Spatial":[100],"Pyramid":[101],"Pooling":[102],"(ASPP)":[103],"final":[106],"layer":[107],"pre-trained":[110],"residual":[111],"capture":[114],"contextual":[116],"at":[118],"different":[119],"scales;":[120],"other":[123],"low-level":[125],"concatenated":[128],"ensure":[130],"sensibility":[132],"small":[134],"targets.":[135],"Furthermore,":[136],"resulting":[138],"multi-level":[139],"recalibrated":[142],"channels":[144],"irrelevant":[146],"suppression":[148],"enhancing":[150],"regions,":[153],"guiding":[154],"adapt":[158],"traces.":[162],"decoder":[165],"module,":[166],"attentive":[168],"feature":[169],"maps":[170],"convoluted":[172],"unsampled":[174],"effectively":[176],"generate":[177],"prediction":[179],"mask.":[180],"Experimental":[181],"results":[182],"indicate":[183],"proposed":[186],"outperforms":[188],"some":[189],"state-of-the-art":[190],"methods.":[192]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":4}],"updated_date":"2026-07-22T07:51:19.307946","created_date":"2025-10-10T00:00:00"}