{"id":"W2112724657","doi":"10.1109/tsmcb.2009.2014245","title":"Color Face Recognition for Degraded Face Images","year":2009,"lang":"en","type":"article","venue":"IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)","topic":"Face and Expression Recognition","field":"Computer Science","cited_by":111,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University; University of Toronto","funders":"National Institute of Standards and Technology","keywords":"Face (sociological concept); Computer vision; Artificial intelligence; Facial recognition system; Computer science; Pattern recognition (psychology); Sociology","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":[0.0007056537,0.000447449,0.0005657497,0.0008900054,0.0002510898,0.0005299943,0.0004244322,0.0004249316,0.003224249],"category_scores_gemma":[0.002460375,0.0001236958,0.0004734791,0.0004739548,0.0003135304,0.0006721206,0.0004641663,0.0004332392,0.00138556],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003693093,"about_ca_system_score_gemma":0.0003178677,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001502222,"about_ca_topic_score_gemma":0.001780413,"domain_scores_codex":[0.9994829,0.0001100427,0.00001693553,0.0001179702,0.000214397,0.00005787608],"domain_scores_gemma":[0.9994981,0.0001449219,0.00005479796,0.00009922543,0.0001825312,0.00002041518],"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":[0.0005831693,0.0001164741,0.003467453,0.000182857,0.00006516988,0.0002422112,0.0001550666,0.01837461,0.2352996,0.003443987,0.003587178,0.7344822],"study_design_scores_gemma":[0.00002524859,0.0004459133,0.03429039,0.00004957645,0.0001063058,0.002120713,0.0002182244,0.7104915,0.2373157,0.006516817,0.008328894,0.00009083995],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2757346,0.001043671,0.713335,0.0002961271,0.0001624087,0.000136445,0.0003879498,0.002422723,0.006481023],"genre_scores_gemma":[0.721555,0.0006653988,0.2735224,0.00019821,0.0000647823,0.00007847222,0.0004891519,0.0001027381,0.003323853],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003224249,"threshold_uncertainty_score":0.01078618,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03242392006122321,"score_gpt":0.2534927829636623,"score_spread":0.2210688629024391,"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."}}