{"id":"https://openalex.org/W4388624620","doi":"https://doi.org/10.1109/lsp.2023.3332506","title":"An Image Steganoganalyzer With Comprehensive Detection Performance","display_name":"An Image Steganoganalyzer With Comprehensive Detection Performance","publication_year":2023,"publication_date":"2023-01-01","ids":{"openalex":"https://openalex.org/W4388624620","doi":"https://doi.org/10.1109/lsp.2023.3332506"},"language":"en","primary_location":{"id":"doi:10.1109/lsp.2023.3332506","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lsp.2023.3332506","pdf_url":null,"source":{"id":"https://openalex.org/S120629676","display_name":"IEEE Signal Processing Letters","issn_l":"1070-9908","issn":["1070-9908","1558-2361"],"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 Signal Processing Letters","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/A5100623011","display_name":"Jian He","orcid":"https://orcid.org/0009-0002-9961-7774"},"institutions":[{"id":"https://openalex.org/I83791580","display_name":"Fujian University of Technology","ror":"https://ror.org/03c8fdb16","country_code":"CN","type":"education","lineage":["https://openalex.org/I83791580"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jian He","raw_affiliation_strings":["School of Electronic, Electrical Engineering and Physics, Fujian University of Technology, Fuzhou, China","School of Electronic, Electrical Engineering and Physics, Fujian University of Technology,, Fuzhou, China"],"raw_orcid":"https://orcid.org/0009-0002-9961-7774","affiliations":[{"raw_affiliation_string":"School of Electronic, Electrical Engineering and Physics, Fujian University of Technology, Fuzhou, China","institution_ids":["https://openalex.org/I83791580"]},{"raw_affiliation_string":"School of Electronic, Electrical Engineering and Physics, Fujian University of Technology,, Fuzhou, China","institution_ids":["https://openalex.org/I83791580"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5070111961","display_name":"Shaowei Weng","orcid":"https://orcid.org/0000-0003-1037-7699"},"institutions":[{"id":"https://openalex.org/I83791580","display_name":"Fujian University of Technology","ror":"https://ror.org/03c8fdb16","country_code":"CN","type":"education","lineage":["https://openalex.org/I83791580"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shaowei Weng","raw_affiliation_strings":["Fujian Provincial Key Laboratory of Big Data Mining and Applications, Fujian University of Technology, Fuzhou, China"],"raw_orcid":"https://orcid.org/0000-0003-1037-7699","affiliations":[{"raw_affiliation_string":"Fujian Provincial Key Laboratory of Big Data Mining and Applications, Fujian University of Technology, Fuzhou, China","institution_ids":["https://openalex.org/I83791580"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5067543068","display_name":"Lifang Yu","orcid":"https://orcid.org/0000-0002-0508-7526"},"institutions":[{"id":"https://openalex.org/I4210135483","display_name":"Beijing Institute of Graphic Communication","ror":"https://ror.org/03yg3v757","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210135483"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lifang Yu","raw_affiliation_strings":["Department of Information Engineering, Beijing Institute of Graphic Communication, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-0508-7526","affiliations":[{"raw_affiliation_string":"Department of Information Engineering, Beijing Institute of Graphic Communication, Beijing, China","institution_ids":["https://openalex.org/I4210135483"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100439759","display_name":"Chunyu Zhang","orcid":"https://orcid.org/0009-0001-1525-1895"},"institutions":[{"id":"https://openalex.org/I165225704","display_name":"Xizang Minzu University","ror":"https://ror.org/042170a43","country_code":"CN","type":"education","lineage":["https://openalex.org/I165225704"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chunyu Zhang","raw_affiliation_strings":["College of Information Engineering, Xizang Minzu University, Xianyang, China","College of information engineering, Xizang Minzu university, Xianyang, China"],"raw_orcid":"https://orcid.org/0009-0001-1525-1895","affiliations":[{"raw_affiliation_string":"College of Information Engineering, Xizang Minzu University, Xianyang, China","institution_ids":["https://openalex.org/I165225704"]},{"raw_affiliation_string":"College of information engineering, Xizang Minzu university, Xianyang, China","institution_ids":["https://openalex.org/I165225704"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100344435","display_name":"Wei Chen","orcid":"https://orcid.org/0000-0002-4335-2319"},"institutions":[{"id":"https://openalex.org/I83791580","display_name":"Fujian University of Technology","ror":"https://ror.org/03c8fdb16","country_code":"CN","type":"education","lineage":["https://openalex.org/I83791580"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei Chen","raw_affiliation_strings":["School of Electronic, Electrical Engineering and Physics, Fujian University of Technology, Fuzhou, China","School of Electronic, Electrical Engineering and Physics, Fujian University of Technology,, Fuzhou, China"],"raw_orcid":"https://orcid.org/0000-0002-4335-2319","affiliations":[{"raw_affiliation_string":"School of Electronic, Electrical Engineering and Physics, Fujian University of Technology, Fuzhou, China","institution_ids":["https://openalex.org/I83791580"]},{"raw_affiliation_string":"School of Electronic, Electrical Engineering and Physics, Fujian University of Technology,, Fuzhou, China","institution_ids":["https://openalex.org/I83791580"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.3473,"has_fulltext":false,"cited_by_count":12,"citation_normalized_percentile":{"value":0.83511186,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":99},"biblio":{"volume":"30","issue":null,"first_page":"1682","last_page":"1686"},"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":0.9969000220298767,"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":0.9886000156402588,"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":0.9210723638534546},{"id":"https://openalex.org/keywords/steganography","display_name":"Steganography","score":0.7419207692146301},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6782478094100952},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.5482431650161743},{"id":"https://openalex.org/keywords/pooling","display_name":"Pooling","score":0.5285828709602356},{"id":"https://openalex.org/keywords/preprocessor","display_name":"Preprocessor","score":0.5078745484352112},{"id":"https://openalex.org/keywords/detector","display_name":"Detector","score":0.5062836408615112},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.48109763860702515},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.47546929121017456},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4695604145526886},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.46182969212532043},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.4272347688674927},{"id":"https://openalex.org/keywords/signal","display_name":"SIGNAL (programming language)","score":0.4264914095401764},{"id":"https://openalex.org/keywords/residual","display_name":"Residual","score":0.4119192063808441},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.22481027245521545},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.18617740273475647},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.11471277475357056}],"concepts":[{"id":"https://openalex.org/C107368093","wikidata":"https://www.wikidata.org/wiki/Q448176","display_name":"Steganalysis","level":4,"score":0.9210723638534546},{"id":"https://openalex.org/C108801101","wikidata":"https://www.wikidata.org/wiki/Q15032","display_name":"Steganography","level":3,"score":0.7419207692146301},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6782478094100952},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.5482431650161743},{"id":"https://openalex.org/C70437156","wikidata":"https://www.wikidata.org/wiki/Q7228652","display_name":"Pooling","level":2,"score":0.5285828709602356},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.5078745484352112},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.5062836408615112},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.48109763860702515},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.47546929121017456},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4695604145526886},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.46182969212532043},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.4272347688674927},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.4264914095401764},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.4119192063808441},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.22481027245521545},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.18617740273475647},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.11471277475357056},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/lsp.2023.3332506","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lsp.2023.3332506","pdf_url":null,"source":{"id":"https://openalex.org/S120629676","display_name":"IEEE Signal Processing Letters","issn_l":"1070-9908","issn":["1070-9908","1558-2361"],"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 Signal Processing Letters","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/17","display_name":"Partnerships for the goals","score":0.49000000953674316}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":25,"referenced_works":["https://openalex.org/W22271197","https://openalex.org/W1976570511","https://openalex.org/W2009130368","https://openalex.org/W2046180645","https://openalex.org/W2081564928","https://openalex.org/W2170598445","https://openalex.org/W2192227561","https://openalex.org/W2194775991","https://openalex.org/W2322622188","https://openalex.org/W2542290803","https://openalex.org/W2621048556","https://openalex.org/W2791370475","https://openalex.org/W2892948265","https://openalex.org/W2960139675","https://openalex.org/W2963957509","https://openalex.org/W2969585684","https://openalex.org/W2981408784","https://openalex.org/W3035502324","https://openalex.org/W3046549894","https://openalex.org/W3133932568","https://openalex.org/W3173290060","https://openalex.org/W4225274170","https://openalex.org/W4293057081","https://openalex.org/W4312540108","https://openalex.org/W4386047745"],"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/W2068740952","https://openalex.org/W1583147569","https://openalex.org/W2182496537","https://openalex.org/W2792878404","https://openalex.org/W3154843532"],"abstract_inverted_index":{"Effectively":[0],"enhancing":[1,51],"the":[2,8,22,52,61,85,90,93,105,133,143,148,155,166,172,176,184,201],"weak":[3,190],"stego":[4,53,94,144,191],"signal":[5,54,95,145],"while":[6,59,108],"striking":[7],"balance":[9],"among":[10,99],"three":[11,62,203],"evaluation":[12],"metrics,":[13],"i.e.,":[14],"detection":[15,67,196,221],"accuracy,":[16],"time":[17],"cost,":[18],"as":[19,21,55,57],"well":[20],"number":[23,86],"of":[24,87,92,137,150,200],"parameters":[25,210],"(NP)":[26],"is":[27,47,211],"indeed":[28],"a":[29,41,78,111,123],"huge":[30],"challenge":[31],"for":[32,83],"existing":[33],"deep":[34],"learning-based":[35],"steganalysis":[36,43,229],"detectors.":[37,230],"In":[38,69],"this":[39],"letter,":[40],"novel":[42],"detector":[44],"called":[45],"GFS-Net":[46,205,218],"proposed,":[48],"aiming":[49],"at":[50],"much":[56],"possible":[58],"balancing":[60],"metrics":[63],"to":[64,132,140,164],"obtain":[65],"comprehensive":[66],"performance.":[68],"preprocessing,":[70],"combining":[71],"highly":[72],"lightweight":[73],"gated":[74],"channel":[75],"transformation":[76],"with":[77,119,206],"pointwise":[79],"convolution":[80,121],"layer":[81],"used":[82],"enlarging":[84],"channels":[88],"enriches":[89],"expression":[91],"by":[96,146],"promoting":[97],"cooperation":[98],"enlarged":[100],"channels,":[101],"thereby":[102],"significantly":[103],"improving":[104],"signal-to-noise":[106],"ratio":[107],"avoiding":[109],"occupying":[110],"large":[112],"NP.":[113],"Moreover,":[114],"two":[115,135],"FasterNet":[116],"blocks":[117],"equipped":[118],"partial":[120],"having":[122],"small":[124],"NP,":[125],"rather":[126],"than":[127,227],"residual":[128],"blocks,":[129],"are":[130,160],"applied":[131],"last":[134],"layers":[136],"feature":[138],"extraction":[139],"efficiently":[141],"extract":[142],"reducing":[147],"calculation":[149],"similar":[151],"features,":[152],"so":[153],"that":[154,217],"computational":[156,225],"cost":[157,226],"and":[158,181,193,223],"NP":[159],"saved.":[161],"Finally,":[162],"compared":[163],"using":[165],"global":[167,177],"average":[168],"pooling":[169,180],"(GAP)":[170],"alone,":[171],"stylepooling":[173],"jointly":[174],"utilizing":[175],"standard":[178],"deviation":[179],"GAP":[182],"helps":[183],"subsequent":[185],"fully":[186],"connected":[187],"better":[188],"identify":[189],"signal,":[192],"thus":[194],"improves":[195],"accuracy.":[197],"By":[198],"means":[199],"above":[202],"perspectives,":[204],"only":[207],"0.13":[208],"M":[209],"obtained.":[212],"Experimental":[213],"results":[214],"also":[215],"demonstrate":[216],"achieves":[219],"higher":[220],"accuracy":[222],"lower":[224],"state-of-the-art":[228]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":4}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
