{"id":"W1965772718","doi":"10.1109/icsmc.2010.5642391","title":"Locally adaptive texture features for multispectral face recognition","year":2010,"lang":"en","type":"article","venue":"","topic":"Face and Expression Recognition","field":"Computer Science","cited_by":45,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"","keywords":"Pattern recognition (psychology); Artificial intelligence; Computer science; Facial recognition system; Subspace topology; Kernel (algebra); Multispectral image; Computer vision; 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":[0.0002498023,0.0002805903,0.0004643495,0.0009187546,0.0001726027,0.0004633942,0.0004607673,0.000365464,0.002967918],"category_scores_gemma":[0.0008310031,0.0001247452,0.0004685366,0.0009080964,0.0002279831,0.0008041637,0.0004106933,0.0004729689,0.001039581],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002878541,"about_ca_system_score_gemma":0.0002191867,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009724795,"about_ca_topic_score_gemma":0.00129622,"domain_scores_codex":[0.9997323,0.00004436581,0.00001221071,0.00003722588,0.0001500383,0.00002385585],"domain_scores_gemma":[0.9997248,0.00007921825,0.00003207491,0.00005825161,0.00009081751,0.00001484465],"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":[0.0001289012,0.00006159594,0.00089097,0.0001762388,0.00004140214,0.0001240015,0.00003468098,0.01863774,0.1280995,0.005476002,0.003667458,0.8426616],"study_design_scores_gemma":[0.00004003286,0.000270689,0.009348124,0.00005327841,0.00009047927,0.001331433,0.00008877842,0.8296237,0.1153632,0.01434055,0.02935536,0.0000944081],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03258835,0.001807826,0.9606994,0.0002132876,0.0001310385,0.00006403543,0.0002743333,0.001144064,0.003077732],"genre_scores_gemma":[0.4380114,0.001656725,0.5528221,0.0001704521,0.0002182905,0.0001744147,0.001092272,0.0002278783,0.005626601],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002967918,"threshold_uncertainty_score":0.009928703,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01695796103607174,"score_gpt":0.2498121752195206,"score_spread":0.2328542141834489,"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."}}