{"id":"W7117576018","doi":"10.1109/icscn67106.2025.11308307","title":"Efficient Face Morphing and Demorphing with Explainable AI using FSGAN","year":2025,"lang":"","type":"article","venue":"","topic":"Face recognition and analysis","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Morphing; Biometrics; Identity (music); Facial recognition system; Face (sociological concept); Cosine similarity; Classifier (UML); Pattern recognition (psychology)","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":[0.000218981,0.0005815817,0.0003031595,0.0002438038,0.0001497568,0.0003170862,0.0005425704,0.0003883473,0.001499834],"category_scores_gemma":[0.0004058691,0.000165003,0.0005573276,0.0001393455,0.0003785686,0.0005427341,0.0005296547,0.0007078356,0.0004644328],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000300494,"about_ca_system_score_gemma":0.0002703745,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001578512,"about_ca_topic_score_gemma":0.002650317,"domain_scores_codex":[0.9998507,0.0000237777,0.000004951486,0.00004705636,0.00004758296,0.00002582263],"domain_scores_gemma":[0.999903,0.00002580453,0.00001327711,0.00003331419,0.00001782527,0.000006762587],"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":[0.0002604665,0.00009974466,0.002320552,0.0001506871,0.0001439374,0.0003033597,0.0001366893,0.2395216,0.1853553,0.01373224,0.004023177,0.5539522],"study_design_scores_gemma":[0.000007662168,0.00008026251,0.0008840912,0.000008804387,0.00002583946,0.0002777529,0.00002264338,0.9549326,0.03750628,0.003634054,0.00260464,0.00001549038],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07868204,0.0004700907,0.9137895,0.0002471932,0.00007953795,0.00007608327,0.000107605,0.002334472,0.004213466],"genre_scores_gemma":[0.7584544,0.0003311036,0.233186,0.0002754874,0.00003634799,0.00007794794,0.0003962948,0.0001534433,0.00708884],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001578512,"threshold_uncertainty_score":0.005017459,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01455859639422048,"score_gpt":0.254220853074334,"score_spread":0.2396622566801135,"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."}}