{"id":"W4384103470","doi":"10.22214/ijraset.2023.54675","title":"Find Missing Person using HAAR CASCADE","year":2023,"lang":"en","type":"article","venue":"International Journal for Research in Applied Science and Engineering Technology","topic":"COVID-19 diagnosis using AI","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Computer science; Haar-like features; Identification (biology); Cascade; Artificial intelligence; Face (sociological concept); Process (computing); Cover (algebra); Haar; Machine learning; Computer vision; Data mining; Facial recognition system; Face detection; Pattern recognition (psychology); Engineering; Operating system","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":[0.000795639,0.001453777,0.001247341,0.002251031,0.0007203107,0.0008498763,0.001485643,0.001312324,0.004502507],"category_scores_gemma":[0.001295936,0.0005431916,0.001201784,0.001087267,0.0003118668,0.001084609,0.000987449,0.001249468,0.003785756],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003010517,"about_ca_system_score_gemma":0.0006104265,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004141501,"about_ca_topic_score_gemma":0.00444141,"domain_scores_codex":[0.9989886,0.00008860479,0.00003498942,0.0002648764,0.0004658816,0.0001570416],"domain_scores_gemma":[0.9994674,0.00008356039,0.00003945224,0.00009435263,0.0002735477,0.00004164425],"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":[0.0005332738,0.0002326876,0.005357591,0.0002339883,0.0002794458,0.0007771215,0.0001383387,0.02713688,0.09662705,0.001880412,0.01074403,0.8560591],"study_design_scores_gemma":[0.0000222612,0.0002704317,0.007800817,0.00005282294,0.0001676927,0.001445669,0.0001425178,0.9245192,0.05790002,0.002107413,0.005522386,0.00004870618],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05384703,0.001178485,0.9333203,0.0003186829,0.0004171067,0.0001915529,0.0004555355,0.00330578,0.006965602],"genre_scores_gemma":[0.5343195,0.001260598,0.4523336,0.0003675135,0.0002256349,0.00009309342,0.001197089,0.0001580235,0.01004494],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004502507,"threshold_uncertainty_score":0.01506239,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1738888810819288,"score_gpt":0.4702060472038425,"score_spread":0.2963171661219136,"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."}}