{"id":"W2591555609","doi":"10.1109/icci-cc.2016.7862022","title":"Image-to-image face recognition using Dual Linear Regression based Classification and Electoral College voting","year":2016,"lang":"en","type":"article","venue":"","topic":"Face and Expression Recognition","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Northern British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Face (sociological concept); Artificial intelligence; Voting; Pattern recognition (psychology); Computer science; Facial recognition system; Image (mathematics); Similarity (geometry); Benchmark (surveying); Pixel; Contextual image classification; Dual (grammatical number); Computer vision; Geography","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":[],"consensus_categories":[],"category_scores_codex":[0.0003082295,0.0001611676,0.000139965,0.0001811735,0.0002330034,0.0001197008,0.0001648597,0.00009449384,0.00008446752],"category_scores_gemma":[0.0001834503,0.0001069822,0.0000388899,0.0003447817,0.0000407886,0.001136132,0.0001176185,0.00008307525,0.0002212672],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005932195,"about_ca_system_score_gemma":0.00006221725,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001920081,"about_ca_topic_score_gemma":0.000007848311,"domain_scores_codex":[0.9985904,0.0001254001,0.0002530325,0.0004935486,0.0002573918,0.0002802082],"domain_scores_gemma":[0.9991094,0.0001539939,0.0001196598,0.0002398262,0.0002187815,0.0001583024],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002992026,0.00003874907,0.000235598,0.00001477926,0.000002876663,0.000006117104,0.00004802343,0.000002088871,0.9526243,0.00008311291,0.002066775,0.04484768],"study_design_scores_gemma":[0.00116486,0.0001466223,0.003530598,0.0005805995,0.00001129353,0.00002328335,0.0001018251,0.6474431,0.3457188,0.0003454353,0.000513942,0.0004196107],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3250399,0.000006881728,0.671719,0.002398984,0.000132052,0.0002104545,0.00001793261,0.0001781796,0.0002965989],"genre_scores_gemma":[0.5904173,0.00000413817,0.4089496,0.0003559737,0.00007236162,0.00001420516,0.00001070924,0.00001266813,0.0001630225],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.647441,"threshold_uncertainty_score":0.4362608,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0542428880676587,"score_gpt":0.295144665666524,"score_spread":0.2409017775988653,"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."}}