{"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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0005012665,0.0002105707,0.0002348475,0.0002213899,0.0002136163,0.00007419186,0.0001603593,0.0001079769,0.00004276413],"category_scores_gemma":[0.00004158778,0.0002152907,0.00006139603,0.001060507,0.00002967634,0.000186848,0.00002434289,0.0002955634,0.001823382],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002131441,"about_ca_system_score_gemma":0.00001888353,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001158079,"about_ca_topic_score_gemma":0.0000415408,"domain_scores_codex":[0.9985938,0.00008883942,0.0004091944,0.0003227307,0.0002019668,0.0003834467],"domain_scores_gemma":[0.9993014,0.00008881341,0.00008632598,0.0003441019,0.00009243356,0.00008690136],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001545328,0.0000151199,0.000630966,0.0006216342,0.00002856696,0.00003026801,0.00194122,0.9721742,0.02113436,0.0001216524,0.00007133968,0.003215273],"study_design_scores_gemma":[0.00003791429,0.00004415304,0.00002376694,0.0003396949,0.00001744793,0.0000499441,0.003362765,0.8955075,0.09877846,0.00002414981,0.001563313,0.0002508499],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7985972,0.0002675739,0.1958526,0.00003055312,0.0007250805,0.0004747591,0.00002736383,0.001904383,0.002120465],"genre_scores_gemma":[0.9989116,0.0000393879,0.0004142309,0.000003279295,0.0001427635,0.00004069175,0.0001184288,0.00007051639,0.000259111],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2003144,"threshold_uncertainty_score":0.9989538,"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."}}