{"id":"W2121340607","doi":"10.4304/jmm.1.1.9-15","title":"Invariant Robust 3-D Face Recognition based on the Hilbert Transform in Spectral Space","year":2006,"lang":"en","type":"article","venue":"Journal of Multimedia","topic":"Face and Expression Recognition","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Research Council Canada","funders":"","keywords":"Invariant (physics); Computer science; Facial recognition system; Hilbert space; Artificial intelligence; Hilbert transform; Pattern recognition (psychology); Mathematics; Computer vision; Pure mathematics","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":[0.0004310534,0.000258629,0.0004675279,0.0005889744,0.0001569874,0.0004315521,0.0004125849,0.000335329,0.001949549],"category_scores_gemma":[0.001085751,0.0001442402,0.0004181975,0.0004692403,0.0004414347,0.0007773826,0.0004444837,0.0004030715,0.0008441858],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002524956,"about_ca_system_score_gemma":0.0002928176,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008049123,"about_ca_topic_score_gemma":0.0006767735,"domain_scores_codex":[0.9996897,0.00007131892,0.0000135418,0.0000442068,0.0001561089,0.00002506745],"domain_scores_gemma":[0.9996736,0.0001372572,0.00003604299,0.0000588721,0.00007987813,0.00001442932],"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":[0.0002573323,0.0000964853,0.001106202,0.0001596376,0.00007423567,0.0001963972,0.0001443188,0.03901758,0.2344168,0.02119494,0.004071703,0.6992644],"study_design_scores_gemma":[0.00002454295,0.0002315556,0.004532976,0.00002498095,0.00003599597,0.001227795,0.00006683375,0.8593124,0.1107218,0.01480923,0.008918113,0.00009383644],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01546662,0.0002214098,0.9823924,0.00007079212,0.00003304813,0.00002729389,0.00005959226,0.0006296559,0.001099167],"genre_scores_gemma":[0.3570515,0.0007061119,0.6389788,0.0001468213,0.00008186274,0.0001222624,0.0003277022,0.0001108026,0.002474197],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001949549,"threshold_uncertainty_score":0.006521881,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02207023508301608,"score_gpt":0.2191947902136074,"score_spread":0.1971245551305913,"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."}}