{"id":"W2118271890","doi":"10.1109/fuzzy.2010.5584450","title":"Enhanced weakly trained frontal face detector for surveillance purposes","year":2010,"lang":"en","type":"article","venue":"","topic":"Face and Expression Recognition","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Detector; Artificial intelligence; Histogram; Computer science; Face (sociological concept); Face detection; False positive rate; Pattern recognition (psychology); Computer vision; Histogram of oriented gradients; Haar-like features; Object-class detection; Facial recognition system; Image (mathematics); Telecommunications","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":[0.0007157653,0.0004719473,0.0007201418,0.0006588921,0.000237592,0.0005033874,0.0007069272,0.0006377523,0.00358911],"category_scores_gemma":[0.001069734,0.0002479233,0.0004707485,0.0003269379,0.0001910078,0.0005669665,0.0004384705,0.0006205486,0.002242395],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003903394,"about_ca_system_score_gemma":0.0005935701,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001454444,"about_ca_topic_score_gemma":0.002294945,"domain_scores_codex":[0.9996526,0.00005044182,0.00001298174,0.00008414594,0.0001492464,0.00005063586],"domain_scores_gemma":[0.9995127,0.0001109491,0.00002728356,0.00007465896,0.0002464508,0.0000280564],"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":[0.0004889257,0.0002652591,0.003423359,0.0001029997,0.00009933196,0.0001785031,0.00004018552,0.01816376,0.3288965,0.001686741,0.007423808,0.6392306],"study_design_scores_gemma":[0.00001884644,0.0002164196,0.005523104,0.00001443895,0.00007199536,0.0006335486,0.00002422706,0.83156,0.1548779,0.0007787755,0.006247974,0.00003288909],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08160681,0.0009296673,0.9095025,0.0001901802,0.0002197874,0.00009054262,0.0003315168,0.00287476,0.004254104],"genre_scores_gemma":[0.5696519,0.0007985919,0.414613,0.0003230364,0.0001214265,0.00008132415,0.001289658,0.0001098837,0.01301113],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00358911,"threshold_uncertainty_score":0.01200682,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01014952682784928,"score_gpt":0.2385279268955054,"score_spread":0.2283784000676561,"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."}}