{"id":"W4362647548","doi":"10.1109/icsca57840.2023.10087584","title":"Deep learning based DeepFake video detection","year":2023,"lang":"en","type":"article","venue":"","topic":"Face recognition and analysis","field":"Computer Science","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Moncton","funders":"","keywords":"Computer science; Deep learning; Field (mathematics); Artificial intelligence; Transfer of learning; Data science; Categorization; Harm; Extortion; Machine learning; Face (sociological concept); Social media; Spotting; Closed captioning; Deep neural networks; Computer security; Image (mathematics); World Wide Web","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001963978,0.000054141,0.00006176089,0.0002085282,0.0001317184,0.0001032179,0.0001571866,0.00002911883,0.000173969],"category_scores_gemma":[0.00005961456,0.00004888177,0.00006946339,0.00112762,0.000007628095,0.0001832042,0.00004561612,0.00007614204,0.002121213],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001453144,"about_ca_system_score_gemma":0.00000920588,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001735493,"about_ca_topic_score_gemma":0.00008325591,"domain_scores_codex":[0.9993793,0.00005046112,0.00008784467,0.0001884094,0.000144921,0.0001490344],"domain_scores_gemma":[0.9996817,0.00006560929,0.00002458983,0.0001327381,0.0000422462,0.0000531045],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000001441856,0.00001546405,0.0004881649,0.000007452804,0.00001497147,0.00001088003,0.00009887715,0.02558053,0.005624901,0.0006118641,0.0001851547,0.9673603],"study_design_scores_gemma":[0.0001042964,0.00001772722,0.001097264,0.000002861349,0.000003501929,0.000001116799,0.00004487409,0.9843465,0.01088872,0.0002989986,0.00312071,0.00007342932],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.006594912,0.000006150301,0.9887674,0.0006033147,0.00009041194,0.00002542377,4.711616e-8,0.0008960215,0.003016253],"genre_scores_gemma":[0.9920622,0.000008973281,0.005765272,0.0003431349,0.00002043738,0.000007731534,0.000003239459,0.000004287868,0.001784692],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9854673,"threshold_uncertainty_score":0.9986557,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01412312200304081,"score_gpt":0.2310234903968903,"score_spread":0.2169003683938495,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}