{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0005537974,0.000371228,0.0004529468,0.0005867235,0.001034036,0.001354904,0.0004440123,0.0001118187,0.0001301977],"category_scores_gemma":[0.00006286663,0.0003170286,0.0001115123,0.002083697,0.0001639058,0.0004586841,0.0005655892,0.0003295339,0.00002628466],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001341605,"about_ca_system_score_gemma":0.0003696003,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004079315,"about_ca_topic_score_gemma":0.00006283131,"domain_scores_codex":[0.9973707,0.000132599,0.0004441641,0.0009638166,0.000409983,0.000678781],"domain_scores_gemma":[0.9987268,0.0001517242,0.0001428877,0.0005111489,0.0002357327,0.0002316578],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00006670452,0.0005960052,0.004397678,0.0007989489,0.0008122578,0.0003349757,0.004953355,0.7986058,0.009705462,0.03097476,0.0004213754,0.1483327],"study_design_scores_gemma":[0.0006711524,0.00004960326,0.0001330617,0.0006931092,0.0001722933,0.00004644985,0.002160541,0.991172,0.004030125,0.0002294564,0.0002336248,0.0004085628],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2583424,0.0006514624,0.7346032,0.003346006,0.0001563396,0.0001961943,0.000001513938,0.00009056931,0.002612275],"genre_scores_gemma":[0.9552501,0.00006538411,0.03943327,0.002015606,0.0000259326,0.000005027133,9.73432e-7,0.00001358285,0.003190086],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6969077,"threshold_uncertainty_score":0.9999282,"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."}}