{"id":"https://openalex.org/W4405271385","doi":"https://doi.org/10.1109/cvmi61877.2024.10782175","title":"Deepfake detection and classification using local surface geometrical features","display_name":"Deepfake detection and classification using local surface geometrical features","publication_year":2024,"publication_date":"2024-10-19","ids":{"openalex":"https://openalex.org/W4405271385","doi":"https://doi.org/10.1109/cvmi61877.2024.10782175"},"language":"en","primary_location":{"id":"doi:10.1109/cvmi61877.2024.10782175","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvmi61877.2024.10782175","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Computer Vision and Machine Intelligence (CVMI)","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/A5115395262","display_name":"M Sivabalamurugan","orcid":null},"institutions":[{"id":"https://openalex.org/I81556334","display_name":"Amrita Vishwa Vidyapeetham","ror":"https://ror.org/03am10p12","country_code":"IN","type":"education","lineage":["https://openalex.org/I81556334"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"M Sivabalamurugan","raw_affiliation_strings":["Amrita Vishwa Vidyapeetham,Amrita School of Computing,Department of Computer Science and Engineering,Coimbatore,India"],"affiliations":[{"raw_affiliation_string":"Amrita Vishwa Vidyapeetham,Amrita School of Computing,Department of Computer Science and Engineering,Coimbatore,India","institution_ids":["https://openalex.org/I81556334"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5021930904","display_name":"T. Swapna","orcid":null},"institutions":[{"id":"https://openalex.org/I81556334","display_name":"Amrita Vishwa Vidyapeetham","ror":"https://ror.org/03am10p12","country_code":"IN","type":"education","lineage":["https://openalex.org/I81556334"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"T R Swapna","raw_affiliation_strings":["Amrita Vishwa Vidyapeetham,Amrita School of Computing,Department of Computer Science and Engineering,Coimbatore,India"],"affiliations":[{"raw_affiliation_string":"Amrita Vishwa Vidyapeetham,Amrita School of Computing,Department of Computer Science and Engineering,Coimbatore,India","institution_ids":["https://openalex.org/I81556334"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5115395262"],"corresponding_institution_ids":["https://openalex.org/I81556334"],"apc_list":null,"apc_paid":null,"fwci":0.5036,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.67436656,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.9634000062942505,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.9634000062942505,"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/T14319","display_name":"Currency Recognition and Detection","score":0.9103999733924866,"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/T14339","display_name":"Image Processing and 3D Reconstruction","score":0.9052000045776367,"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":0.6024472117424011},{"id":"https://openalex.org/keywords/surface","display_name":"Surface (topology)","score":0.4766446053981781},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.44809630513191223},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3989485204219818},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.16178220510482788},{"id":"https://openalex.org/keywords/geometry","display_name":"Geometry","score":0.08733764290809631}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6024472117424011},{"id":"https://openalex.org/C2776799497","wikidata":"https://www.wikidata.org/wiki/Q484298","display_name":"Surface (topology)","level":2,"score":0.4766446053981781},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.44809630513191223},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3989485204219818},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.16178220510482788},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.08733764290809631}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cvmi61877.2024.10782175","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvmi61877.2024.10782175","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Computer Vision and Machine Intelligence (CVMI)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5400000214576721,"display_name":"Climate action","id":"https://metadata.un.org/sdg/13"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W2130258210","https://openalex.org/W3011820288","https://openalex.org/W3110018800","https://openalex.org/W3204893173","https://openalex.org/W3210532231","https://openalex.org/W4213449918","https://openalex.org/W4295357640","https://openalex.org/W4304208062","https://openalex.org/W4312568719","https://openalex.org/W4312661067","https://openalex.org/W4321185916","https://openalex.org/W4387493138","https://openalex.org/W4389742134","https://openalex.org/W4390551568","https://openalex.org/W4392400374","https://openalex.org/W4394842561","https://openalex.org/W6794971112"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2033914206","https://openalex.org/W2042327336"],"abstract_inverted_index":{"The":[0],"rise":[1],"of":[2,12,75,94,113,140,151,158],"deepfake":[3,31,54,101,119,141],"technology":[4],"presents":[5],"a":[6,26,90,134,144],"critical":[7],"challenge":[8],"to":[9,147],"the":[10,16,41,45,64,68,104,111,138,149,156],"integrity":[11],"digital":[13,159],"media,":[14],"prompting":[15],"need":[17],"for":[18,29,72,103],"advanced":[19],"forgery":[20,33],"detection":[21,42],"techniques.":[22],"This":[23,107],"paper":[24],"proposes":[25],"novel":[27],"approach":[28,115],"detecting":[30,117],"image":[32],"by":[34,53],"integrating":[35],"local":[36,49,123],"surface":[37,50,124],"geometry":[38,51,125],"analysis":[39,126],"into":[40],"process.":[43],"Leveraging":[44],"inherent":[46],"alterations":[47],"in":[48,98,116,137],"caused":[52],"generation,":[55],"our":[56,87,114,131],"method":[57,88,132],"extracts":[58],"and":[59,85,154],"merges":[60],"this":[61],"information":[62],"with":[63,127],"original":[65],"image,":[66],"enhancing":[67],"discriminative":[69],"features":[70],"essential":[71],"accurate":[73],"identification":[74],"manipulated":[76,152],"content.":[77,120],"Using":[78],"classification":[79,105],"networks":[80],"such":[81],"as":[82],"Resnet,":[83],"Densenet,":[84],"Efficient,":[86],"achieves":[89],"remarkable":[91],"accuracy":[92,109],"rate":[93],"above":[95],"$98":[96],"\\%$":[97],"correctly":[99],"identifying":[100],"images":[102],"models.":[106],"high":[108],"underscores":[110],"effectiveness":[112],"sophisticated":[118],"By":[121],"combining":[122],"deep":[128],"learning-based":[129],"classification,":[130],"represents":[133],"significant":[135],"advancement":[136],"field":[139],"detection,":[142],"offering":[143],"promising":[145],"solution":[146],"combat":[148],"proliferation":[150],"media":[153],"preserve":[155],"authenticity":[157],"imagery.":[160]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1}],"updated_date":"2026-03-25T14:56:36.534964","created_date":"2025-10-10T00:00:00"}
