{"id":"https://openalex.org/W2949862294","doi":"https://doi.org/10.1109/tifs.2019.2922229","title":"An Embedding Cost Learning Framework Using GAN","display_name":"An Embedding Cost Learning Framework Using GAN","publication_year":2019,"publication_date":"2019-06-12","ids":{"openalex":"https://openalex.org/W2949862294","doi":"https://doi.org/10.1109/tifs.2019.2922229","mag":"2949862294"},"language":"en","primary_location":{"id":"doi:10.1109/tifs.2019.2922229","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tifs.2019.2922229","pdf_url":null,"source":{"id":"https://openalex.org/S61310614","display_name":"IEEE Transactions on Information Forensics and Security","issn_l":"1556-6013","issn":["1556-6013","1556-6021"],"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 Information Forensics and Security","raw_type":"journal-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/A5102991695","display_name":"Jianhua Yang","orcid":"https://orcid.org/0000-0003-0925-1730"},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jianhua Yang","raw_affiliation_strings":["Guangdong Key Laboratory of Information Security, Sun Yat-sen University, Guangzhou, China"],"raw_orcid":"https://orcid.org/0000-0003-0925-1730","affiliations":[{"raw_affiliation_string":"Guangdong Key Laboratory of Information Security, Sun Yat-sen University, Guangzhou, China","institution_ids":["https://openalex.org/I157773358"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5001924092","display_name":"Danyang Ruan","orcid":"https://orcid.org/0000-0001-5980-8600"},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Danyang Ruan","raw_affiliation_strings":["Guangdong Key Laboratory of Information Security, Sun Yat-sen University, Guangzhou, China"],"raw_orcid":"https://orcid.org/0000-0001-5980-8600","affiliations":[{"raw_affiliation_string":"Guangdong Key Laboratory of Information Security, Sun Yat-sen University, Guangzhou, China","institution_ids":["https://openalex.org/I157773358"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5047964483","display_name":"Jiwu Huang","orcid":"https://orcid.org/0000-0002-7625-5689"},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiwu Huang","raw_affiliation_strings":["National Engineering Laboratory for Big Data System Computing Technology, Shenzhen University, Shenzhen, China"],"raw_orcid":"https://orcid.org/0000-0002-7625-5689","affiliations":[{"raw_affiliation_string":"National Engineering Laboratory for Big Data System Computing Technology, Shenzhen University, Shenzhen, China","institution_ids":["https://openalex.org/I180726961"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5077333494","display_name":"Xiangui Kang","orcid":"https://orcid.org/0000-0002-3134-0353"},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiangui Kang","raw_affiliation_strings":["Guangdong Key Laboratory of Information Security, Sun Yat-sen University, Guangzhou, China"],"raw_orcid":"https://orcid.org/0000-0002-3134-0353","affiliations":[{"raw_affiliation_string":"Guangdong Key Laboratory of Information Security, Sun Yat-sen University, Guangzhou, China","institution_ids":["https://openalex.org/I157773358"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5111876760","display_name":"Yun-Qing Shi","orcid":null},"institutions":[{"id":"https://openalex.org/I118118575","display_name":"New Jersey Institute of Technology","ror":"https://ror.org/05e74xb87","country_code":"US","type":"education","lineage":["https://openalex.org/I118118575"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yun-Qing Shi","raw_affiliation_strings":["Department of ECE, New Jersey Institute of Technology, Newark, NJ, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of ECE, New Jersey Institute of Technology, Newark, NJ, USA","institution_ids":["https://openalex.org/I118118575"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":11.6049,"has_fulltext":false,"cited_by_count":262,"citation_normalized_percentile":{"value":0.99058603,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":100},"biblio":{"volume":"15","issue":null,"first_page":"839","last_page":"851"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10388","display_name":"Advanced Steganography and Watermarking Techniques","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/T10388","display_name":"Advanced Steganography and Watermarking Techniques","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/T12357","display_name":"Digital Media Forensic Detection","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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","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"}}],"keywords":[{"id":"https://openalex.org/keywords/steganography","display_name":"Steganography","score":0.9005184173583984},{"id":"https://openalex.org/keywords/steganalysis","display_name":"Steganalysis","score":0.8539760112762451},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.7736074328422546},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7604032754898071},{"id":"https://openalex.org/keywords/discriminator","display_name":"Discriminator","score":0.6011626124382019},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5285947322845459},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5133165717124939},{"id":"https://openalex.org/keywords/backpropagation","display_name":"Backpropagation","score":0.5089614391326904},{"id":"https://openalex.org/keywords/distortion","display_name":"Distortion (music)","score":0.4398949146270752},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.4135058522224426},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.37246644496917725},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.36995550990104675},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.34463319182395935},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.32407140731811523},{"id":"https://openalex.org/keywords/bandwidth","display_name":"Bandwidth (computing)","score":0.10765713453292847},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.08489811420440674}],"concepts":[{"id":"https://openalex.org/C108801101","wikidata":"https://www.wikidata.org/wiki/Q15032","display_name":"Steganography","level":3,"score":0.9005184173583984},{"id":"https://openalex.org/C107368093","wikidata":"https://www.wikidata.org/wiki/Q448176","display_name":"Steganalysis","level":4,"score":0.8539760112762451},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.7736074328422546},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7604032754898071},{"id":"https://openalex.org/C2779803651","wikidata":"https://www.wikidata.org/wiki/Q5282088","display_name":"Discriminator","level":3,"score":0.6011626124382019},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5285947322845459},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5133165717124939},{"id":"https://openalex.org/C155032097","wikidata":"https://www.wikidata.org/wiki/Q798503","display_name":"Backpropagation","level":3,"score":0.5089614391326904},{"id":"https://openalex.org/C126780896","wikidata":"https://www.wikidata.org/wiki/Q899871","display_name":"Distortion (music)","level":4,"score":0.4398949146270752},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.4135058522224426},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.37246644496917725},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.36995550990104675},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.34463319182395935},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.32407140731811523},{"id":"https://openalex.org/C2776257435","wikidata":"https://www.wikidata.org/wiki/Q1576430","display_name":"Bandwidth (computing)","level":2,"score":0.10765713453292847},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.08489811420440674},{"id":"https://openalex.org/C194257627","wikidata":"https://www.wikidata.org/wiki/Q211554","display_name":"Amplifier","level":3,"score":0.0},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tifs.2019.2922229","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tifs.2019.2922229","pdf_url":null,"source":{"id":"https://openalex.org/S61310614","display_name":"IEEE Transactions on Information Forensics and Security","issn_l":"1556-6013","issn":["1556-6013","1556-6021"],"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 Information Forensics and Security","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","score":0.7400000095367432,"id":"https://metadata.un.org/sdg/10"}],"awards":[{"id":"https://openalex.org/G4414785203","display_name":null,"funder_award_id":"U1636202","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7248977280","display_name":null,"funder_award_id":"61772571","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8895439857","display_name":null,"funder_award_id":"U1536204","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":38,"referenced_works":["https://openalex.org/W22271197","https://openalex.org/W1836465849","https://openalex.org/W1901129140","https://openalex.org/W1955882805","https://openalex.org/W1965064373","https://openalex.org/W1976570511","https://openalex.org/W2009130368","https://openalex.org/W2031466562","https://openalex.org/W2046180645","https://openalex.org/W2081564928","https://openalex.org/W2099471712","https://openalex.org/W2106663508","https://openalex.org/W2124664712","https://openalex.org/W2134527668","https://openalex.org/W2170598445","https://openalex.org/W2192227561","https://openalex.org/W2194775991","https://openalex.org/W2296073425","https://openalex.org/W2322622188","https://openalex.org/W2416075718","https://openalex.org/W2514127746","https://openalex.org/W2538511122","https://openalex.org/W2542290803","https://openalex.org/W2621048556","https://openalex.org/W2735904389","https://openalex.org/W2751202750","https://openalex.org/W2791370475","https://openalex.org/W2793291280","https://openalex.org/W2892948265","https://openalex.org/W2962951125","https://openalex.org/W2963073614","https://openalex.org/W2963446712","https://openalex.org/W2963682422","https://openalex.org/W2963957509","https://openalex.org/W4320013936","https://openalex.org/W6638667902","https://openalex.org/W6639824700","https://openalex.org/W6662048488"],"related_works":["https://openalex.org/W2148973528","https://openalex.org/W2939392096","https://openalex.org/W4243922849","https://openalex.org/W2106726851","https://openalex.org/W4309385482","https://openalex.org/W2792878404","https://openalex.org/W2068740952","https://openalex.org/W1583147569","https://openalex.org/W2182496537","https://openalex.org/W3154843532"],"abstract_inverted_index":{"Successful":[0],"adaptive":[1,28],"steganography":[2],"has":[3,24,32,54],"mainly":[4],"focused":[5],"on":[6,99,116],"embedding":[7,70,82],"the":[8,35,38,80,91,111,122,126,132,141],"payload":[9],"while":[10,84],"minimizing":[11],"an":[12,69,95],"appropriately":[13],"defined":[14],"distortion":[15,46,145],"function.":[16],"The":[17],"application":[18],"of":[19,40],"deep":[20],"learning":[21,146],"to":[22,63,78],"steganalysis":[23],"greatly":[25],"challenged":[26],"present":[27],"steganographic":[29,129,144],"methods,":[30],"but":[31],"also":[33],"shown":[34,120],"potential":[36],"for":[37,51],"improvement":[39],"steganography.":[41,52],"This":[42],"paper":[43],"proposes":[44],"a":[45,49,57,60,65,74,100],"function":[47,77],"generating":[48],"framework":[50,124,147],"It":[53],"three":[55],"modules:":[56],"generator":[58],"with":[59,105,140],"U-Net":[61],"architecture":[62],"translate":[64],"cover":[66],"image":[67],"into":[68],"change":[71],"probability":[72],"map,":[73],"no-pre-training-required":[75],"double-tanh":[76],"approximate":[79],"optimal":[81],"simulator":[83],"preserving":[85],"gradient":[86],"norm":[87],"during":[88],"backpropagation":[89],"in":[90],"adversarial":[92,133],"training,":[93],"and":[94],"enhanced":[96],"steganalyzer":[97],"based":[98],"convolution":[101],"neural":[102],"network":[103],"together":[104],"multiple":[106],"high":[107],"pass":[108],"filters":[109],"as":[110],"discriminator.":[112],"Extensive":[113],"experimental":[114],"results":[115],"different":[117],"datasets":[118],"have":[119],"that":[121],"proposed":[123],"outperforms":[125],"current":[127],"state-of-the-art":[128],"schemes.":[130],"Moreover,":[131],"training":[134],"time":[135],"is":[136],"reduced":[137],"dramatically":[138],"compared":[139],"GAN-based":[142],"automatic":[143],"(ASDL-GAN).":[148]},"counts_by_year":[{"year":2026,"cited_by_count":8},{"year":2025,"cited_by_count":43},{"year":2024,"cited_by_count":55},{"year":2023,"cited_by_count":53},{"year":2022,"cited_by_count":33},{"year":2021,"cited_by_count":37},{"year":2020,"cited_by_count":24},{"year":2019,"cited_by_count":8},{"year":2012,"cited_by_count":1}],"updated_date":"2026-07-25T09:21:30.201066","created_date":"2025-10-10T00:00:00"}
