{"id":"W4388474381","doi":"10.18280/ria.370510","title":"Room Security System Using Machine Learning with Face Recognition Verification","year":2023,"lang":"en","type":"article","venue":"Revue d intelligence artificielle","topic":"IoT-based Smart Home Systems","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Facial recognition system; Computer science; Face (sociological concept); Artificial intelligence; Face Recognition Grand Challenge; Security system; Machine learning; Computer security; Pattern recognition (psychology); Human–computer interaction; Face detection; Sociology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006797467,0.0005919518,0.0006798765,0.0006215572,0.0003980207,0.0005214449,0.001052695,0.0006201864,0.004682849],"category_scores_gemma":[0.001094869,0.0002203926,0.0005769754,0.0002438452,0.0002482507,0.001113256,0.001010607,0.0004592751,0.001926938],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005858637,"about_ca_system_score_gemma":0.0008848609,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001859989,"about_ca_topic_score_gemma":0.001476455,"domain_scores_codex":[0.9991303,0.00009303382,0.00004374302,0.0002674635,0.0003694429,0.00009604069],"domain_scores_gemma":[0.9995561,0.0000663872,0.00005808652,0.00009402002,0.0001894416,0.00003600196],"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":[0.001179894,0.0005284438,0.0108105,0.0002122502,0.0001304714,0.0007226849,0.00019028,0.03991794,0.250858,0.004020435,0.00603071,0.6853983],"study_design_scores_gemma":[0.00004682516,0.0006915039,0.005881532,0.00003009492,0.00007147356,0.0006229366,0.00004697061,0.8426754,0.1435989,0.001128162,0.005125124,0.00008112691],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2308406,0.000331433,0.7410687,0.0002846708,0.0002430396,0.0005743421,0.000341954,0.01776065,0.008554481],"genre_scores_gemma":[0.8756902,0.00007853319,0.1187482,0.0001084307,0.00002583454,0.000188281,0.0003268278,0.00008077111,0.004753096],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004682849,"threshold_uncertainty_score":0.01566565,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03821553404044625,"score_gpt":0.2377162521787479,"score_spread":0.1995007181383017,"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."}}