{"id":"W4415515869","doi":"10.1007/978-3-032-07373-0_3","title":"Facial Spoof Detection Using Deep Learning Techniques for Enhanced Biometric Security","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Biometric Identification and Security","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université de Moncton","funders":"","keywords":"Liveness; Spoofing attack; Biometrics; Convolutional neural network; Deep learning; Authentication (law); Vulnerability (computing); Facial recognition system","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002060744,0.0003898266,0.0003143696,0.0003869748,0.0001050478,0.0004120547,0.0003593219,0.0004724875,0.003976872],"category_scores_gemma":[0.000331605,0.0001549116,0.000327573,0.0003379316,0.000185147,0.0006334571,0.000480547,0.0005874853,0.001509846],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002654567,"about_ca_system_score_gemma":0.0002124899,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000963747,"about_ca_topic_score_gemma":0.001884765,"domain_scores_codex":[0.9998662,0.00001312083,0.000005567436,0.00002517661,0.00007025241,0.00001964194],"domain_scores_gemma":[0.9998986,0.00002770259,0.00001118178,0.0000174466,0.00004084848,0.00000418077],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001416834,0.00006838432,0.0006023077,0.0001231062,0.00003480334,0.00009670305,0.00003596099,0.01844121,0.1811003,0.005397716,0.00587955,0.7880783],"study_design_scores_gemma":[0.000005885708,0.0001274552,0.002169566,0.00004994423,0.00004457864,0.0004959464,0.00002508139,0.8265011,0.150301,0.004284315,0.01596574,0.00002950923],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05916388,0.003211146,0.9223153,0.0003512215,0.0002806665,0.00004185069,0.000259211,0.001456268,0.01292036],"genre_scores_gemma":[0.5737393,0.005078649,0.3665278,0.0002918775,0.0001497821,0.00005162129,0.0006800742,0.0002004308,0.05328052],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003976872,"threshold_uncertainty_score":0.013304,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03878836484766509,"score_gpt":0.3157351913628646,"score_spread":0.2769468265151995,"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."}}