{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001581948,0.000215723,0.0002677553,0.005493619,0.0009822585,0.0008771258,0.002510246,0.0002249265,0.000003478526],"category_scores_gemma":[0.0002276507,0.0002390314,0.00007851557,0.003027764,0.0004939041,0.004572248,0.001557583,0.0004539081,0.000008108674],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003258272,"about_ca_system_score_gemma":0.0002668297,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002436259,"about_ca_topic_score_gemma":0.00001424357,"domain_scores_codex":[0.9981863,0.0000444017,0.0007429847,0.0003711092,0.0004109906,0.0002441441],"domain_scores_gemma":[0.9970273,0.0002949368,0.0004711791,0.001284694,0.0008416557,0.00008025278],"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":[0.000002654928,0.00001585878,0.000005582349,0.00005401643,0.000005302145,4.435491e-8,0.001074515,0.00002105684,0.00008982729,0.1464739,0.00001307698,0.8522441],"study_design_scores_gemma":[0.0002299873,0.00005705961,0.000166819,0.000106615,0.000009314985,0.000006553966,0.00002340415,0.7585339,0.001589282,0.008413796,0.2305234,0.000339858],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00007987694,0.0003017517,0.9648908,0.0001287537,0.0003991309,0.0006189316,0.00001295193,0.0001714752,0.03339634],"genre_scores_gemma":[0.3813896,0.003841185,0.6119665,0.0006330794,0.00009919145,0.0001305744,0.0001377273,0.00001600789,0.001786122],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.8519043,"threshold_uncertainty_score":0.9747418,"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."}}