{"id":"https://openalex.org/W2514127746","doi":"https://doi.org/10.1109/icip.2016.7532860","title":"Learning and transferring representations for image steganalysis using convolutional neural network","display_name":"Learning and transferring representations for image steganalysis using convolutional neural network","publication_year":2016,"publication_date":"2016-08-17","ids":{"openalex":"https://openalex.org/W2514127746","doi":"https://doi.org/10.1109/icip.2016.7532860","mag":"2514127746"},"language":"en","primary_location":{"id":"doi:10.1109/icip.2016.7532860","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2016.7532860","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE International Conference on Image Processing (ICIP)","raw_type":"proceedings-article"},"type":"article","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/A5038795686","display_name":"Yinlong Qian","orcid":null},"institutions":[{"id":"https://openalex.org/I4210142635","display_name":"PATH To Reading","ror":"https://ror.org/0482xmh13","country_code":"US","type":"other","lineage":["https://openalex.org/I4210142635"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Yinlong Qian","raw_affiliation_strings":["Center for Research on Intelligent Perception and Computing, Chinese Academy of Sciences"],"affiliations":[{"raw_affiliation_string":"Center for Research on Intelligent Perception and Computing, Chinese Academy of Sciences","institution_ids":["https://openalex.org/I4210142635"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5017743261","display_name":"Jing Dong","orcid":"https://orcid.org/0000-0002-2763-7832"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jing Dong","raw_affiliation_strings":["State Key Laboratory of Information Security, Chinese Academy of Sciences"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Information Security, Chinese Academy of Sciences","institution_ids":["https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100757829","display_name":"Wei Wang","orcid":"https://orcid.org/0000-0002-8598-0831"},"institutions":[{"id":"https://openalex.org/I4210142635","display_name":"PATH To Reading","ror":"https://ror.org/0482xmh13","country_code":"US","type":"other","lineage":["https://openalex.org/I4210142635"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Wei Wang","raw_affiliation_strings":["Center for Research on Intelligent Perception and Computing, Chinese Academy of Sciences"],"affiliations":[{"raw_affiliation_string":"Center for Research on Intelligent Perception and Computing, Chinese Academy of Sciences","institution_ids":["https://openalex.org/I4210142635"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5111885963","display_name":"Tieniu Tan","orcid":null},"institutions":[{"id":"https://openalex.org/I4210142635","display_name":"PATH To Reading","ror":"https://ror.org/0482xmh13","country_code":"US","type":"other","lineage":["https://openalex.org/I4210142635"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Tieniu Tan","raw_affiliation_strings":["Center for Research on Intelligent Perception and Computing, Chinese Academy of Sciences"],"affiliations":[{"raw_affiliation_string":"Center for Research on Intelligent Perception and Computing, Chinese Academy of Sciences","institution_ids":["https://openalex.org/I4210142635"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5038795686"],"corresponding_institution_ids":["https://openalex.org/I4210142635"],"apc_list":null,"apc_paid":null,"fwci":10.657,"has_fulltext":false,"cited_by_count":158,"citation_normalized_percentile":{"value":0.98899387,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"2752","last_page":"2756"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10388","display_name":"Advanced Steganography and Watermarking Techniques","score":0.9998999834060669,"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/T10388","display_name":"Advanced Steganography and Watermarking Techniques","score":0.9998999834060669,"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/T12357","display_name":"Digital Media Forensic Detection","score":0.9991000294685364,"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":0.9933000206947327,"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/steganalysis","display_name":"Steganalysis","score":0.9867541790008545},{"id":"https://openalex.org/keywords/steganography","display_name":"Steganography","score":0.8749884366989136},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.8255703449249268},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7827211618423462},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7266882061958313},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.653407096862793},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.605676531791687},{"id":"https://openalex.org/keywords/payload","display_name":"Payload (computing)","score":0.5937581062316895},{"id":"https://openalex.org/keywords/transfer-of-learning","display_name":"Transfer of learning","score":0.5418378710746765},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5136470198631287},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5084661245346069},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4675876796245575},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.45098409056663513},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.34692323207855225},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.06017163395881653}],"concepts":[{"id":"https://openalex.org/C107368093","wikidata":"https://www.wikidata.org/wiki/Q448176","display_name":"Steganalysis","level":4,"score":0.9867541790008545},{"id":"https://openalex.org/C108801101","wikidata":"https://www.wikidata.org/wiki/Q15032","display_name":"Steganography","level":3,"score":0.8749884366989136},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.8255703449249268},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7827211618423462},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7266882061958313},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.653407096862793},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.605676531791687},{"id":"https://openalex.org/C134066672","wikidata":"https://www.wikidata.org/wiki/Q1424639","display_name":"Payload (computing)","level":3,"score":0.5937581062316895},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.5418378710746765},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5136470198631287},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5084661245346069},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4675876796245575},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.45098409056663513},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.34692323207855225},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.06017163395881653},{"id":"https://openalex.org/C158379750","wikidata":"https://www.wikidata.org/wiki/Q214111","display_name":"Network packet","level":2,"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":1,"locations":[{"id":"doi:10.1109/icip.2016.7532860","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2016.7532860","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE International Conference on Image Processing (ICIP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":27,"referenced_works":["https://openalex.org/W22271197","https://openalex.org/W29798142","https://openalex.org/W103335665","https://openalex.org/W1502609557","https://openalex.org/W1590456553","https://openalex.org/W1665214252","https://openalex.org/W1983364832","https://openalex.org/W2009130368","https://openalex.org/W2016053056","https://openalex.org/W2040299224","https://openalex.org/W2046180645","https://openalex.org/W2059019537","https://openalex.org/W2071451750","https://openalex.org/W2112796928","https://openalex.org/W2123170991","https://openalex.org/W2124664712","https://openalex.org/W2145038566","https://openalex.org/W2161381512","https://openalex.org/W2538511122","https://openalex.org/W2542290803","https://openalex.org/W2548753991","https://openalex.org/W6630132114","https://openalex.org/W6637242042","https://openalex.org/W6662048488","https://openalex.org/W6668300802","https://openalex.org/W6729295898","https://openalex.org/W6730109398"],"related_works":["https://openalex.org/W4243922849","https://openalex.org/W2939392096","https://openalex.org/W2148973528","https://openalex.org/W2930153478","https://openalex.org/W4309385482","https://openalex.org/W2040931326","https://openalex.org/W2792878404","https://openalex.org/W1583147569","https://openalex.org/W2068740952","https://openalex.org/W2182496537"],"abstract_inverted_index":{"The":[0],"major":[1],"challenge":[2],"of":[3,57,94],"machine":[4],"learning":[5,29,52,93,126],"based":[6,49],"image":[7],"steganalysis":[8],"lies":[9],"in":[10,43,122,127],"obtaining":[11],"powerful":[12],"feature":[13,70,125],"representations.":[14],"Recently,":[15],"Qian":[16],"et":[17],"al.":[18],"have":[19],"shown":[20],"that":[21,69,116],"Convolutional":[22],"Neural":[23],"Network":[24],"(CNN)":[25],"is":[26,120],"effective":[27,121],"for":[28,32,59,77,96,130],"features":[30,95],"automatically":[31],"steganalysis.":[33,131],"In":[34],"this":[35,40],"paper,":[36],"we":[37,114],"follow":[38],"up":[39],"new":[41],"paradigm":[42],"steganalysis,":[44,60],"and":[45,110],"propose":[46],"a":[47,64,74,79,83,103],"framework":[48],"on":[50],"transfer":[51],"to":[53,62,90],"help":[54],"the":[55,92,98,117,124],"training":[56],"CNN":[58,76,128],"hence":[61],"achieve":[63],"better":[65],"performance.":[66],"We":[67],"show":[68],"representations":[71],"learned":[72],"with":[73,82,102],"pre-trained":[75],"detecting":[78,97,107],"steganographic":[80,100,112],"algorithm":[81,101],"high":[84],"payload":[85],"can":[86],"be":[87],"efficiently":[88],"transferred":[89],"improve":[91],"same":[99],"low":[104],"pay-load.":[105],"By":[106],"representative":[108],"WOW":[109],"S-UNIWARD":[111],"algorithms,":[113],"demonstrate":[115],"proposed":[118],"scheme":[119],"improving":[123],"models":[129]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":10},{"year":2024,"cited_by_count":10},{"year":2023,"cited_by_count":16},{"year":2022,"cited_by_count":18},{"year":2021,"cited_by_count":17},{"year":2020,"cited_by_count":23},{"year":2019,"cited_by_count":25},{"year":2018,"cited_by_count":21},{"year":2017,"cited_by_count":16},{"year":2016,"cited_by_count":1}],"updated_date":"2026-03-05T09:29:38.588285","created_date":"2025-10-10T00:00:00"}
