{"id":"https://openalex.org/W4391331122","doi":"https://doi.org/10.1145/3634875.3634888","title":"Faster R-CNN image splicing tampering detection based on multilayer feature refinement fusion","display_name":"Faster R-CNN image splicing tampering detection based on multilayer feature refinement fusion","publication_year":2023,"publication_date":"2023-10-20","ids":{"openalex":"https://openalex.org/W4391331122","doi":"https://doi.org/10.1145/3634875.3634888"},"language":"en","primary_location":{"id":"doi:10.1145/3634875.3634888","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3634875.3634888","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2023 8th International Conference on Biomedical Imaging, Signal Processing","raw_type":"proceedings-article"},"type":"conference-paper","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/A5090807324","display_name":"Weiyi Wei","orcid":"https://orcid.org/0000-0002-9286-5911"},"institutions":[{"id":"https://openalex.org/I68986083","display_name":"Northwest Normal University","ror":"https://ror.org/00gx3j908","country_code":"CN","type":"education","lineage":["https://openalex.org/I68986083"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weiyi Wei","raw_affiliation_strings":["College of Computer Science and Engineering, Northwest Normal University, China"],"raw_orcid":"https://orcid.org/0000-0002-9286-5911","affiliations":[{"raw_affiliation_string":"College of Computer Science and Engineering, Northwest Normal University, China","institution_ids":["https://openalex.org/I68986083"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5040938774","display_name":"Futong Zhang","orcid":"https://orcid.org/0009-0008-5989-6733"},"institutions":[{"id":"https://openalex.org/I68986083","display_name":"Northwest Normal University","ror":"https://ror.org/00gx3j908","country_code":"CN","type":"education","lineage":["https://openalex.org/I68986083"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Futong Zhang","raw_affiliation_strings":["College of Computer Science and Engineering, Northwest Normal University, China"],"raw_orcid":"https://orcid.org/0009-0008-5989-6733","affiliations":[{"raw_affiliation_string":"College of Computer Science and Engineering, Northwest Normal University, China","institution_ids":["https://openalex.org/I68986083"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101706378","display_name":"Chen Guo","orcid":"https://orcid.org/0009-0005-8742-052X"},"institutions":[{"id":"https://openalex.org/I68986083","display_name":"Northwest Normal University","ror":"https://ror.org/00gx3j908","country_code":"CN","type":"education","lineage":["https://openalex.org/I68986083"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guo Chen","raw_affiliation_strings":["College of Computer Science and Engineering, Northwest Normal University, China"],"raw_orcid":"https://orcid.org/0009-0005-8742-052X","affiliations":[{"raw_affiliation_string":"College of Computer Science and Engineering, Northwest Normal University, China","institution_ids":["https://openalex.org/I68986083"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5113107401","display_name":"Huanhuan Lei","orcid":null},"institutions":[{"id":"https://openalex.org/I68986083","display_name":"Northwest Normal University","ror":"https://ror.org/00gx3j908","country_code":"CN","type":"education","lineage":["https://openalex.org/I68986083"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Huanhuan Lei","raw_affiliation_strings":["College of Computer Science and Engineering, Northwest Normal University, China"],"raw_orcid":"https://orcid.org/0009-0001-5126-9195","affiliations":[{"raw_affiliation_string":"College of Computer Science and Engineering, Northwest Normal University, China","institution_ids":["https://openalex.org/I68986083"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I68986083"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"89","last_page":"96"},"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9930999875068665,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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":0.9909999966621399,"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":0.6973940134048462},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6843960285186768},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5853756666183472},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.5591346621513367},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5495275259017944},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.502392053604126},{"id":"https://openalex.org/keywords/image-fusion","display_name":"Image fusion","score":0.49574407935142517},{"id":"https://openalex.org/keywords/fusion","display_name":"Fusion","score":0.4683862030506134},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.43457236886024475},{"id":"https://openalex.org/keywords/feature-detection","display_name":"Feature detection (computer vision)","score":0.4110834002494812},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.23471176624298096}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6973940134048462},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6843960285186768},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5853756666183472},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.5591346621513367},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5495275259017944},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.502392053604126},{"id":"https://openalex.org/C69744172","wikidata":"https://www.wikidata.org/wiki/Q860822","display_name":"Image fusion","level":3,"score":0.49574407935142517},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.4683862030506134},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.43457236886024475},{"id":"https://openalex.org/C126422989","wikidata":"https://www.wikidata.org/wiki/Q93586","display_name":"Feature detection (computer vision)","level":4,"score":0.4110834002494812},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.23471176624298096},{"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:10.1145/3634875.3634888","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3634875.3634888","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2023 8th International Conference on Biomedical Imaging, Signal Processing","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":14,"referenced_works":["https://openalex.org/W2104657103","https://openalex.org/W2565639579","https://openalex.org/W2603123944","https://openalex.org/W2752015292","https://openalex.org/W2800531694","https://openalex.org/W2963066927","https://openalex.org/W2963091558","https://openalex.org/W2964146055","https://openalex.org/W2975393663","https://openalex.org/W2978985845","https://openalex.org/W3199966831","https://openalex.org/W4210783895","https://openalex.org/W4288710362","https://openalex.org/W6608287133"],"related_works":["https://openalex.org/W2788731446","https://openalex.org/W2204403038","https://openalex.org/W3152170969","https://openalex.org/W2139242969","https://openalex.org/W2379054866","https://openalex.org/W2549658594","https://openalex.org/W2370195708","https://openalex.org/W1490651872","https://openalex.org/W2350422455","https://openalex.org/W2284201331"],"abstract_inverted_index":{"Deep":[0],"learning-based":[1],"methods":[2],"have":[3],"made":[4],"significant":[5],"progress":[6],"in":[7,76,111,167,208],"image":[8,38,85,92,100,196,222],"tampering":[9,40,166,223],"detection.":[10,224],"However,":[11],"they":[12],"often":[13],"overlook":[14],"the":[15,56,70,83,87,90,96,102,138,150,155,161,174,183,202,205,210,219],"characteristics":[16],"of":[17,58,72,163,204,221],"small-size":[18,214],"tampered":[19,74,215],"regions,":[20,216],"leading":[21],"to":[22,54,159,182,218],"missed":[23],"or":[24],"false":[25],"detections.":[26],"To":[27],"address":[28],"these":[29],"issues,":[30],"this":[31],"paper":[32],"proposes":[33],"a":[34,62,112,145],"novel":[35],"approach":[36,52,185],"for":[37,89,101],"splicing":[39,165,197],"detection":[41,179],"using":[42,144],"Faster":[43],"R-CNN,":[44],"which":[45],"incorporates":[46],"multi-layer":[47,63],"feature":[48,64,129],"refinement":[49,65,113,118,122],"fusion.":[50],"This":[51,124],"aims":[53],"enhance":[55,160],"expression":[57],"features":[59,119,136],"by":[60,195],"employing":[61],"fusion":[66,114,125],"strategy,":[67],"thereby":[68],"improving":[69],"accuracy":[71,162,180],"detecting":[73,164],"regions":[75,193],"small":[77,168],"areas.":[78,169],"The":[79,134,199],"proposed":[80,175,206],"method":[81,176,207],"utilizes":[82,127],"RGB":[84,151],"as":[86],"input":[88],"color":[91],"channel":[93],"and":[94],"employs":[95],"SRM":[97],"filter":[98],"processed":[99],"steganographic":[103],"analysis":[104],"channel.":[105],"These":[106],"two":[107,139],"channels":[108,140,152],"are":[109,141],"fused":[110,143],"network,":[115],"combining":[116],"deep":[117],"with":[120,213],"shallow":[121],"features.":[123],"effectively":[126,191],"refined":[128],"information":[130],"from":[131,137],"different":[132],"levels.":[133],"extracted":[135],"further":[142],"bilinear":[146],"pooling":[147],"layer.":[148],"Additionally,":[149],"adaptively":[153],"adjust":[154],"anchor":[156],"frame":[157],"shapes":[158],"Experimental":[170],"results":[171],"demonstrate":[172],"that":[173],"achieves":[177],"im-proved":[178],"compared":[181],"original":[184],"on":[186],"publicly":[187],"available":[188],"datasets.":[189],"It":[190],"detects":[192],"affected":[194],"tampering.":[198],"findings":[200],"highlight":[201],"potential":[203],"addressing":[209],"challenges":[211],"associated":[212],"contributing":[217],"advancement":[220]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
