{"id":"https://openalex.org/W2963235754","doi":"https://doi.org/10.1109/tcyb.2018.2864870","title":"Pornographic Image Recognition via Weighted Multiple Instance Learning","display_name":"Pornographic Image Recognition via Weighted Multiple Instance Learning","publication_year":2018,"publication_date":"2018-09-13","ids":{"openalex":"https://openalex.org/W2963235754","doi":"https://doi.org/10.1109/tcyb.2018.2864870","mag":"2963235754","pmid":"https://pubmed.ncbi.nlm.nih.gov/30222590"},"language":"en","primary_location":{"id":"doi:10.1109/tcyb.2018.2864870","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tcyb.2018.2864870","pdf_url":null,"source":{"id":"https://openalex.org/S4210191041","display_name":"IEEE Transactions on Cybernetics","issn_l":"2168-2267","issn":["2168-2267","2168-2275"],"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 Transactions on Cybernetics","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5023967844","display_name":"Xin Jin","orcid":"https://orcid.org/0000-0001-6655-3888"},"institutions":[{"id":"https://openalex.org/I4401726805","display_name":"Megvii (China)","ror":"https://ror.org/040b32p69","country_code":null,"type":"company","lineage":["https://openalex.org/I4401726805"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xin Jin","raw_affiliation_strings":["Megvii Research Nanjing, Megvii Inc. (Face++), Nanjing, China"],"affiliations":[{"raw_affiliation_string":"Megvii Research Nanjing, Megvii Inc. (Face++), Nanjing, China","institution_ids":["https://openalex.org/I4401726805"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101445664","display_name":"Yuhui Wang","orcid":"https://orcid.org/0000-0001-6581-6826"},"institutions":[{"id":"https://openalex.org/I9842412","display_name":"Nanjing University of Aeronautics and Astronautics","ror":"https://ror.org/01scyh794","country_code":"CN","type":"education","lineage":["https://openalex.org/I9842412"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuhui Wang","raw_affiliation_strings":["Collaborative Innovation Center of Novel Software Technology and Industrialization, Nanjing University of Aeronautics and Astronautics, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"Collaborative Innovation Center of Novel Software Technology and Industrialization, Nanjing University of Aeronautics and Astronautics, Nanjing, China","institution_ids":["https://openalex.org/I9842412"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5004478562","display_name":"Xiaoyang Tan","orcid":"https://orcid.org/0000-0002-2683-8667"},"institutions":[{"id":"https://openalex.org/I9842412","display_name":"Nanjing University of Aeronautics and Astronautics","ror":"https://ror.org/01scyh794","country_code":"CN","type":"education","lineage":["https://openalex.org/I9842412"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaoyang Tan","raw_affiliation_strings":["Collaborative Innovation Center of Novel Software Technology and Industrialization, Nanjing University of Aeronautics and Astronautics, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"Collaborative Innovation Center of Novel Software Technology and Industrialization, Nanjing University of Aeronautics and Astronautics, Nanjing, China","institution_ids":["https://openalex.org/I9842412"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5023967844"],"corresponding_institution_ids":["https://openalex.org/I4401726805"],"apc_list":null,"apc_paid":null,"fwci":2.0892,"has_fulltext":false,"cited_by_count":31,"citation_normalized_percentile":{"value":0.9100705,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":"49","issue":"12","first_page":"4412","last_page":"4420"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11439","display_name":"Video Analysis and Summarization","score":0.9987999796867371,"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/T11439","display_name":"Video Analysis and Summarization","score":0.9987999796867371,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9975000023841858,"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/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9973999857902527,"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":0.7220768928527832},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6892586350440979},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6328686475753784},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5805245637893677},{"id":"https://openalex.org/keywords/pornography","display_name":"Pornography","score":0.5667314529418945},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.5628756284713745},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.5352122783660889},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5311943888664246},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3742002844810486},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.0764254629611969},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.0644107460975647}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7220768928527832},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6892586350440979},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6328686475753784},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5805245637893677},{"id":"https://openalex.org/C2781301322","wikidata":"https://www.wikidata.org/wiki/Q291","display_name":"Pornography","level":2,"score":0.5667314529418945},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.5628756284713745},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.5352122783660889},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5311943888664246},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3742002844810486},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0764254629611969},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0644107460975647},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","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/C11171543","wikidata":"https://www.wikidata.org/wiki/Q41630","display_name":"Psychoanalysis","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tcyb.2018.2864870","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tcyb.2018.2864870","pdf_url":null,"source":{"id":"https://openalex.org/S4210191041","display_name":"IEEE Transactions on Cybernetics","issn_l":"2168-2267","issn":["2168-2267","2168-2275"],"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 Transactions on Cybernetics","raw_type":"journal-article"},{"id":"pmid:30222590","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/30222590","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":"IEEE transactions on cybernetics","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/5","display_name":"Gender equality","score":0.49000000953674316}],"awards":[{"id":"https://openalex.org/G1745238659","display_name":null,"funder_award_id":"61672280","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7529917","display_name":null,"funder_award_id":"61732006","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7687912082","display_name":null,"funder_award_id":"61373060","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8056387268","display_name":null,"funder_award_id":"2017YFB0802300","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program 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/F4320327794","display_name":"Qinglan Project of Jiangsu Province of China","ror":null},{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":51,"referenced_works":["https://openalex.org/W7746136","https://openalex.org/W1480498941","https://openalex.org/W1531235167","https://openalex.org/W1587328194","https://openalex.org/W1968968243","https://openalex.org/W1973212234","https://openalex.org/W1976977741","https://openalex.org/W2007917976","https://openalex.org/W2009243364","https://openalex.org/W2010262905","https://openalex.org/W2012054397","https://openalex.org/W2014046923","https://openalex.org/W2016016818","https://openalex.org/W2035933607","https://openalex.org/W2053037512","https://openalex.org/W2069796578","https://openalex.org/W2075977566","https://openalex.org/W2087544334","https://openalex.org/W2088049833","https://openalex.org/W2096730180","https://openalex.org/W2097117768","https://openalex.org/W2098166271","https://openalex.org/W2102605133","https://openalex.org/W2110119381","https://openalex.org/W2112397370","https://openalex.org/W2117129845","https://openalex.org/W2127744755","https://openalex.org/W2130287785","https://openalex.org/W2135176316","https://openalex.org/W2135502357","https://openalex.org/W2136595724","https://openalex.org/W2151103935","https://openalex.org/W2153493250","https://openalex.org/W2155893237","https://openalex.org/W2160541552","https://openalex.org/W2161967063","https://openalex.org/W2161969291","https://openalex.org/W2163352848","https://openalex.org/W2163605009","https://openalex.org/W2166010828","https://openalex.org/W2167912153","https://openalex.org/W2171839786","https://openalex.org/W2182953902","https://openalex.org/W2328809058","https://openalex.org/W2409697880","https://openalex.org/W6679195402","https://openalex.org/W6680075925","https://openalex.org/W6680240620","https://openalex.org/W6684191040","https://openalex.org/W6685131103","https://openalex.org/W6686173969"],"related_works":["https://openalex.org/W4388064163","https://openalex.org/W4388121746","https://openalex.org/W4254577890","https://openalex.org/W3213019559","https://openalex.org/W1999296022","https://openalex.org/W2049574408","https://openalex.org/W1521439752","https://openalex.org/W3215105932","https://openalex.org/W61207332","https://openalex.org/W2120603743"],"abstract_inverted_index":{"In":[0,46],"the":[1,26,78,98,117,148,160,169,182,196,199],"era":[2],"of":[3,9,43,56,81,97,111,136,140,150,184,198],"Internet,":[4],"recognizing":[5],"pornographic":[6,28,100,218],"images":[7,219],"is":[8,22],"great":[10],"significance":[11],"for":[12],"protecting":[13],"children's":[14],"physical":[15],"and":[16,32,58,83,220],"mental":[17],"health.":[18],"However,":[19],"this":[20,47],"task":[21,162],"very":[23,94],"challenging":[24],"as":[25,53,163],"key":[27,99],"contents":[29,101],"(e.g.,":[30],"breast":[31],"private":[33],"part)":[34],"in":[35,40,102,153],"an":[36,203],"image":[37,52],"often":[38],"lie":[39],"local":[41],"regions":[42,120,152],"small":[44],"size.":[45],"paper,":[48],"we":[49,74,89,106,130,158],"model":[50],"each":[51],"a":[54,60,68,103,109,132,137,154,164,175],"bag":[55,110,176],"regions,":[57,114],"follow":[59],"multiple":[61],"instance":[62],"learning":[63],"(MIL)":[64],"approach":[65],"to":[66,146,180],"train":[67],"generic":[69],"region-based":[70],"recognition":[71,161],"model.":[72],"Specifically,":[73],"take":[75],"into":[76],"account":[77],"regions'":[79],"degree":[80,139],"pornography,":[82,141],"make":[84],"three":[85],"main":[86],"contributions.":[87],"First,":[88],"show":[90],"that":[91,125],"based":[92],"on":[93,188,216],"few":[95],"annotations":[96],"training":[104],"image,":[105],"can":[107,126,143],"generate":[108],"properly":[112],"sized":[113],"among":[115],"which":[116,142],"potential":[118],"positive":[119,155,208,213],"usually":[121],"contain":[122],"useful":[123],"contexts":[124],"aid":[127],"recognition.":[128],"Second,":[129],"present":[131],"simple":[133],"quantitative":[134],"measure":[135],"region's":[138],"be":[144],"used":[145],"weigh":[147],"importance":[149,183],"different":[151,185],"image.":[156],"Third,":[157],"formulate":[159],"weighted":[165],"MIL":[166],"problem":[167],"under":[168],"convolutional":[170],"neural":[171],"network":[172],"framework,":[173],"with":[174,205],"probability":[177],"function":[178],"introduced":[179],"combine":[181],"regions.":[186],"Experiments":[187],"our":[189],"newly":[190],"collected":[191],"large":[192],"scale":[193],"dataset":[194],"demonstrate":[195],"effectiveness":[197],"proposed":[200],"method,":[201],"achieving":[202],"accuracy":[204],"97.52%":[206],"true":[207],"rate":[209],"at":[210],"1%":[211],"false":[212],"rate,":[214],"tested":[215],"100K":[217,221],"normal":[222],"images.":[223]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":7},{"year":2020,"cited_by_count":4},{"year":2019,"cited_by_count":8},{"year":2018,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}