{"id":"https://openalex.org/W4410073479","doi":"https://doi.org/10.55041/ijsrem46928","title":"\u201cImage Forgery Detection Using Transfer Learning\u201d","display_name":"\u201cImage Forgery Detection Using Transfer Learning\u201d","publication_year":2025,"publication_date":"2025-05-04","ids":{"openalex":"https://openalex.org/W4410073479","doi":"https://doi.org/10.55041/ijsrem46928"},"language":"en","primary_location":{"id":"doi:10.55041/ijsrem46928","doi":"https://doi.org/10.55041/ijsrem46928","is_oa":true,"landing_page_url":"https://doi.org/10.55041/ijsrem46928","pdf_url":"https://ijsrem.com/download/image-forgery-detection-using-transfer-learning-2/?wpdmdl=51046&refresh=68186496ad9dd1746429078","source":{"id":"https://openalex.org/S4210240841","display_name":"INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT","issn_l":"2582-3930","issn":["2582-3930"],"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"INTERNATIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT","raw_type":"journal-article"},"volume":null,"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"bronze","oa_url":"https://ijsrem.com/download/image-forgery-detection-using-transfer-learning-2/?wpdmdl=51046&refresh=68186496ad9dd1746429078","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5117430026","display_name":"Abbas Asif Tisekar","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Abbas Asif Tisekar","raw_affiliation_strings":["Department of Computer Engineering"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Engineering","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":["https://openalex.org/A5117430026"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.06744944,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"09","issue":"05","first_page":"1","last_page":"9"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12357","display_name":"Digital Media Forensic Detection","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/T12357","display_name":"Digital Media Forensic Detection","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/T10388","display_name":"Advanced Steganography and Watermarking Techniques","score":0.0,"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/T13720","display_name":"Benford\u2019s Law and Fraud Detection","score":0.0,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/image-forgery-detection","display_name":"image forgery detection","score":0.9980000257492065},{"id":"https://openalex.org/keywords/image-forgery","display_name":"image tampering","score":0.9049999713897705},{"id":"https://openalex.org/keywords/transfer-learning","display_name":"transfer learning","score":0.7459999918937683},{"id":"https://openalex.org/keywords/convolutional-neural-networks","display_name":"convolutional neural networks","score":0.8849999904632568},{"id":"https://openalex.org/keywords/copy-move-forgery","display_name":"copy-move forgery","score":0.9440000057220459},{"id":"https://openalex.org/keywords/splicing","display_name":"splicing","score":0.7620000243186951},{"id":"https://openalex.org/keywords/image-removal","display_name":"image removal","score":0.6909999847412109},{"id":"https://openalex.org/keywords/digital-forensics","display_name":"digital forensics","score":0.8709999918937683}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6068905591964722},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5952584147453308},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.560238778591156},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4780628979206085},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4675138592720032},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.38917672634124756}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.55041/ijsrem46928","doi":"https://doi.org/10.55041/ijsrem46928","is_oa":true,"landing_page_url":"https://doi.org/10.55041/ijsrem46928","pdf_url":"https://ijsrem.com/download/image-forgery-detection-using-transfer-learning-2/?wpdmdl=51046&refresh=68186496ad9dd1746429078","source":{"id":"https://openalex.org/S4210240841","display_name":"INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT","issn_l":"2582-3930","issn":["2582-3930"],"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"INTERNATIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.55041/ijsrem46928","doi":"https://doi.org/10.55041/ijsrem46928","is_oa":true,"landing_page_url":"https://doi.org/10.55041/ijsrem46928","pdf_url":"https://ijsrem.com/download/image-forgery-detection-using-transfer-learning-2/?wpdmdl=51046&refresh=68186496ad9dd1746429078","source":{"id":"https://openalex.org/S4210240841","display_name":"INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT","issn_l":"2582-3930","issn":["2582-3930"],"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"INTERNATIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT","raw_type":"journal-article"},"sustainable_development_goals":[],"sustainable_development_goals_aurora":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4410073479.pdf","grobid_xml":"https://content.openalex.org/works/W4410073479.grobid-xml"},"referenced_works_count":10,"referenced_works":["https://openalex.org/W2973188965","https://openalex.org/W3003940567","https://openalex.org/W3187793897","https://openalex.org/W4285240680","https://openalex.org/W4312746849","https://openalex.org/W4386065460","https://openalex.org/W4391097225","https://openalex.org/W4402041065","https://openalex.org/W4402978427","https://openalex.org/W4404371013"],"related_works":["https://openalex.org/W2772917594","https://openalex.org/W2036807459","https://openalex.org/W2058170566","https://openalex.org/W2755342338","https://openalex.org/W2166024367","https://openalex.org/W3116076068","https://openalex.org/W2229312674","https://openalex.org/W2951359407","https://openalex.org/W2079911747","https://openalex.org/W1969923398"],"abstract_inverted_index":{"Abstract:":[0],"In":[1],"today\u2019s":[2],"digital":[3,226,244],"world,":[4],"images":[5,27,52,131,141,189,231],"are":[6,53,69,143,194,232],"often":[7,61],"shared":[8],"and":[9,17,37,83,129,165,172,190,208,225,234],"used":[10],"as":[11,44,162],"evidence":[12],"in":[13,140],"news,":[14],"legal":[15],"cases,":[16],"social":[18],"media.":[19],"However,":[20],"it":[21,176,184],"has":[22],"become":[23],"easier":[24],"to":[25,34,49,105,127,145,228],"manipulate":[26],"using":[28],"editing":[29],"tools,":[30],"which":[31],"can":[32,136,185],"lead":[33],"false":[35,214],"information":[36],"serious":[38],"consequences.":[39],"Detecting":[40],"these":[41],"changes,":[42],"known":[43],"image":[45,59,93,245],"forgery,":[46,160,252],"is":[47,111,168],"important":[48],"make":[50,229],"sure":[51,230],"trustworthy.":[54],"Traditional":[55],"methods":[56,75],"for":[57,156,221],"detecting":[58],"tampering":[60],"struggle":[62],"with":[63,88,147],"accuracy,":[64,207],"especially":[65],"when":[66],"the":[67,89,148,178,199,211],"edits":[68],"small":[70],"or":[71,196],"done":[72],"carefully.":[73],"These":[74,134],"also":[76],"require":[77],"a":[78,98,112,218],"lot":[79],"of":[80,92,159,180,213],"manual":[81],"work":[82],"may":[84],"not":[85],"keep":[86],"up":[87],"fast-growing":[90],"technology":[91],"editing.":[94],"This":[95],"project":[96,203],"presents":[97],"smart":[99],"system":[100,152],"that":[101,116,142],"uses":[102,117],"transfer":[103,240],"learning":[104,110,114,120],"detect":[106],"forged":[107],"images.":[108],"Transfer":[109],"machine":[113,256],"method":[115],"pre-trained":[118],"deep":[119,242],"models,":[121],"like":[122],"CNNs":[123],"(Convolutional":[124],"Neural":[125],"Networks),":[126],"understand":[128],"analyze":[130],"more":[132],"effectively.":[133],"models":[135],"find":[137],"tiny":[138],"changes":[139],"hard":[144],"notice":[146],"human":[149],"eye.":[150],"The":[151],"works":[153],"by":[154],"checking":[155],"common":[157],"types":[158],"such":[161],"copy-move,":[163],"splicing,":[164,253],"removal.":[166],"It":[167,216],"trained":[169],"on":[170],"real":[171,233],"tampered":[173,254],"images,":[174,255],"helping":[175],"learn":[177],"patterns":[179],"forgery.":[181],"Once":[182],"trained,":[183],"quickly":[186],"check":[187],"new":[188],"say":[191],"whether":[192],"they":[193],"original":[195],"fake.By":[197],"automating":[198],"detection":[200,259],"process,":[201],"this":[202],"saves":[204],"time,":[205],"improves":[206],"helps":[209],"fight":[210],"spread":[212],"visuals.":[215],"provides":[217],"reliable":[219],"tool":[220],"media,":[222],"law":[223],"enforcement,":[224],"forensics":[227],"trustworthy.Key":[235],"Words:":[236],"Image":[237],"forgery":[238],"detection,":[239],"learning,":[241,243,257],"forensics,":[246],"convolutional":[247],"neural":[248],"networks":[249],"(CNN),":[250],"copy-move":[251],"automated":[258],"systems":[260]},"counts_by_year":[],"updated_date":"2026-08-23T07:36:19.812096","created_date":"2025-05-05T00:00:00"}