{"id":"W2130288511","doi":"10.1109/ccece.2007.334","title":"Face Recognition Under Significant Pose Variation","year":2007,"lang":"en","type":"article","venue":"","topic":"Face and Expression Recognition","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"Natural Sciences and Engineering Research Council of Canada; Concordia University","keywords":"Artificial intelligence; Computer science; Facial recognition system; Computer vision; Face (sociological concept); Pattern recognition (psychology); AdaBoost; Three-dimensional face recognition; Pose; Face detection; Active appearance model; Variation (astronomy); Image (mathematics); Support vector machine","routes":{"ca_aff":true,"ca_fund":true,"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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0004325554,0.00007909133,0.00006100653,0.0001001951,0.00008515956,0.00009179008,0.0001951961,0.00006873183,0.0002009269],"category_scores_gemma":[0.00002349375,0.00006744247,0.00003355705,0.0002354846,0.00001017965,0.0005735629,0.00005209229,0.00007423227,0.0009593119],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002840833,"about_ca_system_score_gemma":0.000020982,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004083168,"about_ca_topic_score_gemma":0.000009250116,"domain_scores_codex":[0.9991485,0.0000306091,0.0001753451,0.0002425536,0.0002021688,0.0002008052],"domain_scores_gemma":[0.9994814,0.0000895001,0.00005605632,0.0002045567,0.00008771804,0.0000807426],"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":[0.000045742,0.0003590482,0.000152886,0.00001808155,0.00002894308,0.00002517845,0.001693971,0.0001702259,0.2887788,0.03065935,0.01321521,0.6648526],"study_design_scores_gemma":[0.002248361,0.0004398195,0.09572802,0.0001271149,0.00003110844,0.00005333051,0.001503633,0.05319056,0.6028314,0.2345851,0.007847295,0.001414208],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04075122,0.000007061124,0.9419876,0.0008865863,0.000397079,0.0001145894,0.000001254798,0.0002355118,0.01561914],"genre_scores_gemma":[0.9384314,0.000009484393,0.05929669,0.001379272,0.00008188102,0.000005355515,0.00001716641,0.000005550269,0.0007731469],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8976802,"threshold_uncertainty_score":0.9998186,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02839435131818251,"score_gpt":0.2534785585854878,"score_spread":0.2250842072673053,"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."}}