{"id":"https://openalex.org/W2922115507","doi":"https://doi.org/10.23919/apsipa.2018.8659761","title":"Fake Colorized Image Detection with Channel-wise Convolution based Deep-learning Framework","display_name":"Fake Colorized Image Detection with Channel-wise Convolution based Deep-learning Framework","publication_year":2018,"publication_date":"2018-11-01","ids":{"openalex":"https://openalex.org/W2922115507","doi":"https://doi.org/10.23919/apsipa.2018.8659761","mag":"2922115507"},"language":"en","primary_location":{"id":"doi:10.23919/apsipa.2018.8659761","is_oa":false,"landing_page_url":"https://doi.org/10.23919/apsipa.2018.8659761","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC)","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/A5060440457","display_name":"Zhuo Long","orcid":"https://orcid.org/0000-0001-5018-7086"},"institutions":[{"id":"https://openalex.org/I4210144487","display_name":"Cloud Computing Center","ror":"https://ror.org/04aa0zm65","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210144487"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Long Zhuo","raw_affiliation_strings":["Shenzhen Key Laboratory of Media Security, National Engineering Laboratory for Big Data System Computing Technology, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Shenzhen Key Laboratory of Media Security, National Engineering Laboratory for Big Data System Computing Technology, Shenzhen, China","institution_ids":["https://openalex.org/I4210144487"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023503629","display_name":"Shunquan Tan","orcid":"https://orcid.org/0000-0002-7457-3691"},"institutions":[{"id":"https://openalex.org/I4210144487","display_name":"Cloud Computing Center","ror":"https://ror.org/04aa0zm65","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210144487"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shunquan Tan","raw_affiliation_strings":["Shenzhen Key Laboratory of Media Security, National Engineering Laboratory for Big Data System Computing Technology, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Shenzhen Key Laboratory of Media Security, National Engineering Laboratory for Big Data System Computing Technology, Shenzhen, China","institution_ids":["https://openalex.org/I4210144487"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5061167775","display_name":"Jishen Zeng","orcid":"https://orcid.org/0000-0002-4894-9966"},"institutions":[{"id":"https://openalex.org/I4210144487","display_name":"Cloud Computing Center","ror":"https://ror.org/04aa0zm65","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210144487"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jishen Zeng","raw_affiliation_strings":["Shenzhen Key Laboratory of Media Security, National Engineering Laboratory for Big Data System Computing Technology, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Shenzhen Key Laboratory of Media Security, National Engineering Laboratory for Big Data System Computing Technology, Shenzhen, China","institution_ids":["https://openalex.org/I4210144487"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5055964466","display_name":"Bin Lit","orcid":null},"institutions":[{"id":"https://openalex.org/I4210144487","display_name":"Cloud Computing Center","ror":"https://ror.org/04aa0zm65","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210144487"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bin Lit","raw_affiliation_strings":["Shenzhen Key Laboratory of Media Security, National Engineering Laboratory for Big Data System Computing Technology, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Shenzhen Key Laboratory of Media Security, National Engineering Laboratory for Big Data System Computing Technology, Shenzhen, China","institution_ids":["https://openalex.org/I4210144487"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5060440457"],"corresponding_institution_ids":["https://openalex.org/I4210144487"],"apc_list":null,"apc_paid":null,"fwci":0.8357,"has_fulltext":false,"cited_by_count":18,"citation_normalized_percentile":{"value":0.79694634,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"733","last_page":"736"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12357","display_name":"Digital Media Forensic Detection","score":0.9993000030517578,"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":0.9993000030517578,"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":0.9990000128746033,"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":0.9961000084877014,"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":0.7174922823905945},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.7096204161643982},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.7073714733123779},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6437965631484985},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.6280964612960815},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.615743100643158},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.6114802956581116},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4639289975166321},{"id":"https://openalex.org/keywords/detector","display_name":"Detector","score":0.44472914934158325},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.14059704542160034},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.10476928949356079}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7174922823905945},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.7096204161643982},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.7073714733123779},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6437965631484985},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.6280964612960815},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.615743100643158},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.6114802956581116},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4639289975166321},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.44472914934158325},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.14059704542160034},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.10476928949356079},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.23919/apsipa.2018.8659761","is_oa":false,"landing_page_url":"https://doi.org/10.23919/apsipa.2018.8659761","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","score":0.800000011920929,"id":"https://metadata.un.org/sdg/16"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":12,"referenced_works":["https://openalex.org/W1976570511","https://openalex.org/W2009130368","https://openalex.org/W2074727269","https://openalex.org/W2308529009","https://openalex.org/W2326925005","https://openalex.org/W2461158874","https://openalex.org/W2565257220","https://openalex.org/W2784285978","https://openalex.org/W2792207818","https://openalex.org/W3101267198","https://openalex.org/W6698507324","https://openalex.org/W6701655646"],"related_works":["https://openalex.org/W2366906938","https://openalex.org/W4375867731","https://openalex.org/W2349391998","https://openalex.org/W4205655149","https://openalex.org/W2000775715","https://openalex.org/W2074467390","https://openalex.org/W2611989081","https://openalex.org/W2795393339","https://openalex.org/W2626393719","https://openalex.org/W4390618967"],"abstract_inverted_index":{"Colorization":[0],"is":[1,123],"one":[2],"remarkable":[3],"emerging":[4],"image":[5,31,39,94],"manipulating":[6],"technique,":[7],"which":[8,122],"maybe":[9],"potentially":[10],"used":[11],"for":[12],"illegal":[13],"purpose.":[14],"In":[15],"this":[16,69,130],"paper,":[17],"we":[18,102],"introduce":[19],"WISERNet":[20],"(Wider":[21],"Separate-then-reunion":[22],"Network),":[23],"a":[24],"recently":[25],"proposed":[26,79],"deep-learning":[27,57],"based":[28,58],"data-driven":[29,59],"color":[30,120],"steganalyzer":[32],"in":[33,68,99,129],"the":[34,74,109,114],"field":[35],"of":[36,77],"fake":[37,92],"colorized":[38,93],"detection.":[40,95],"We":[41],"believe":[42],"that":[43,98],"statistical":[44],"inconsistencies":[45],"introduced":[46],"by":[47,55],"different":[48,125],"automatic":[49],"colorization":[50],"methods":[51],"can":[52],"be":[53],"captured":[54],"advanced":[56],"color-image":[60],"steganalyzers":[61],"such":[62],"as":[63],"WISERNet.":[64],"Experimental":[65],"evidences":[66],"reported":[67],"paper":[70],"supports":[71],"our":[72,78,100],"claims:":[73],"detection":[75],"performance":[76],"detector":[80],"obviously":[81],"outperforms":[82],"FCID-HIST":[83],"and":[84,118],"FCID-FE,":[85],"two":[86],"state-of-the-art":[87],"hand-crafted":[88],"features":[89],"specific":[90,110],"to":[91],"Please":[96],"note":[97],"approach":[101],"have":[103],"never":[104],"explicitly":[105],"utilized":[106],"information":[107],"from":[108,126],"channels":[111],"other":[112],"than":[113],"ordinary":[115],"red,":[116],"green,":[117],"blue":[119],"channel,":[121],"completely":[124],"prior":[127],"works":[128],"field.":[131]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
