{"id":"W2079467126","doi":"10.1109/crv.2010.20","title":"Multispectral Face Recognition in Texture Space","year":2010,"lang":"en","type":"article","venue":"","topic":"Face and Expression Recognition","field":"Computer Science","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"","keywords":"Multispectral image; Face (sociological concept); Artificial intelligence; Computer science; Computer vision; Texture (cosmology); Facial recognition system; Image texture; Space (punctuation); Pattern recognition (psychology); Image processing; Image (mathematics); Linguistics","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":[0.000225048,0.0002924688,0.0004932849,0.0007707176,0.0001838955,0.0006015188,0.00037053,0.0003455217,0.002927691],"category_scores_gemma":[0.0006458013,0.0001256315,0.0004505883,0.0005627314,0.0002411493,0.0007806404,0.000511595,0.0003020793,0.001428963],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001920798,"about_ca_system_score_gemma":0.0001446213,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00063424,"about_ca_topic_score_gemma":0.0006227725,"domain_scores_codex":[0.9997362,0.00003549664,0.00001055907,0.00004811227,0.0001410602,0.00002842503],"domain_scores_gemma":[0.9997916,0.00004936726,0.00002225855,0.0000474955,0.00007737734,0.00001195557],"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":[0.000225884,0.0001103798,0.0009567718,0.0002035962,0.00004064052,0.0001824872,0.0000809138,0.0154619,0.3210703,0.007616158,0.001996161,0.6520547],"study_design_scores_gemma":[0.00003335818,0.000394166,0.01229495,0.00006371875,0.0001039599,0.002842162,0.0001908766,0.6583534,0.2901128,0.01331554,0.02220641,0.00008857878],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09721932,0.000974587,0.892629,0.0001587005,0.0001723826,0.00006799433,0.0002336638,0.001205693,0.007338603],"genre_scores_gemma":[0.5253303,0.001400674,0.4622675,0.0001664174,0.0001378355,0.0001187908,0.0006057875,0.0001459387,0.009826764],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002927691,"threshold_uncertainty_score":0.009794116,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01095158076249989,"score_gpt":0.2349667149283285,"score_spread":0.2240151341658286,"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."}}