{"id":"W4289321251","doi":"10.18280/rces.090207","title":"Biometrics Face Recognition Using Method of Wavelet and Curvelet Transforms with COVID-19","year":2022,"lang":"en","type":"article","venue":"Review of Computer Engineering Studies","topic":"Face recognition and analysis","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"University of Anbar","keywords":"Facial recognition system; Computer science; Artificial intelligence; Face (sociological concept); Biometrics; Curvelet; Pattern recognition (psychology); Intranet; Three-dimensional face recognition; Face detection; Wavelet transform; Focus (optics); Computer vision; Face Recognition Grand Challenge; Speech recognition; Wavelet; The Internet; World Wide Web","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":[],"consensus_categories":[],"category_scores_codex":[0.0008101811,0.0001445358,0.0005695682,0.0004104364,0.00008152307,0.00001180806,0.0002163434,0.00001347606,0.000006152374],"category_scores_gemma":[0.00007932254,0.0001161313,0.0001009406,0.001848644,0.00002904551,0.0001320261,0.0001879622,0.00009434532,3.052652e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005600958,"about_ca_system_score_gemma":0.00004168482,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000789362,"about_ca_topic_score_gemma":3.140631e-7,"domain_scores_codex":[0.9988747,0.00009355738,0.000367661,0.0002306974,0.0002972773,0.0001360538],"domain_scores_gemma":[0.9991748,0.0002764244,0.0001717814,0.0001735553,0.0001405705,0.00006290436],"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":[0.000007704752,0.0001515524,0.00009294783,0.04021504,0.001269527,0.00002041221,0.002189993,0.05281311,0.0003844922,0.0008008772,0.0004031987,0.9016511],"study_design_scores_gemma":[0.0009409376,0.0005502822,0.0001258745,0.004545737,0.0003775193,0.0002859833,0.0002224551,0.9776745,0.001214164,0.000196186,0.01322299,0.0006433277],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001403584,0.04774505,0.950043,0.0004856379,0.00007040968,0.0001794863,0.0000222526,0.00004634673,0.000004205607],"genre_scores_gemma":[0.01382521,0.05796806,0.9275458,0.0005841914,0.00002036442,0.00002863308,0.00001100763,0.00001321101,0.00000355769],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9248614,"threshold_uncertainty_score":0.4735696,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06608943687841959,"score_gpt":0.3350190491083499,"score_spread":0.2689296122299303,"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."}}