{"id":"W2084269393","doi":"10.1109/cvpr.2014.342","title":"Dual Linear Regression Based Classification for Face Cluster Recognition","year":2014,"lang":"en","type":"article","venue":"","topic":"Face and Expression Recognition","field":"Computer Science","cited_by":58,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Northern British Columbia","funders":"","keywords":"Linear subspace; Face (sociological concept); Artificial intelligence; Pattern recognition (psychology); Facial recognition system; Computer science; Intersection (aeronautics); Subspace topology; Similarity (geometry); Cluster (spacecraft); Relation (database); Computer vision; Mathematics; Image (mathematics); Data mining; Geography; Geometry","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000394109,0.0001126528,0.0001031484,0.00009427157,0.0001517609,0.00008584254,0.0002024977,0.0001093914,0.00005170035],"category_scores_gemma":[0.0001379406,0.00008526313,0.00006798527,0.0001407558,0.00001645573,0.0004734441,0.00004561761,0.00007261522,0.0003418335],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000177285,"about_ca_system_score_gemma":0.00002430482,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003783704,"about_ca_topic_score_gemma":0.000003034607,"domain_scores_codex":[0.9989778,0.00009262712,0.0002014537,0.0003553408,0.0001870955,0.0001857137],"domain_scores_gemma":[0.9991033,0.0002261969,0.00009921463,0.0003295935,0.0001643492,0.00007732687],"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":[0.0001013666,0.0001886549,0.00007736344,0.00007178082,0.00000741261,4.345736e-7,0.0001984798,0.0002000147,0.03615473,0.002833071,0.06680986,0.8933569],"study_design_scores_gemma":[0.0008621981,0.0001218183,0.0002978231,0.00007051071,0.000005153287,0.000001697069,0.00003097407,0.9139738,0.05740186,0.003188149,0.02387579,0.0001701968],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01034527,0.000004246269,0.9807895,0.004504433,0.0003428075,0.0003121014,0.000005201469,0.0002447735,0.003451642],"genre_scores_gemma":[0.6212406,0.000005296214,0.3734831,0.00336786,0.0002408012,0.0001641864,0.0002098804,0.00001607917,0.001272236],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9137738,"threshold_uncertainty_score":0.4393692,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05570834887365179,"score_gpt":0.2873746816249442,"score_spread":0.2316663327512924,"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."}}