{"id":"W4388938770","doi":"10.1111/exsy.13507","title":"An automated face mask detection system using transfer learning based neural network to preventing viral infection","year":2023,"lang":"en","type":"article","venue":"Expert Systems","topic":"Face recognition and analysis","field":"Computer Science","cited_by":37,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Computer science; Artificial intelligence; Haar-like features; Coronavirus disease 2019 (COVID-19); Face detection; Machine learning; Transfer of learning; Artificial neural network; Residual; Process (computing); Deep learning; Train; Computer vision; Pattern recognition (psychology); Facial recognition system; Infectious disease (medical specialty)","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":[0.0003990169,0.0005979714,0.000628743,0.000651321,0.0004006076,0.0004024075,0.0007850426,0.0006813357,0.00278382],"category_scores_gemma":[0.0005995298,0.0002536988,0.0003927282,0.0002015065,0.0001723744,0.0005148248,0.0003878499,0.0003929139,0.000787107],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006795035,"about_ca_system_score_gemma":0.0005859352,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006634749,"about_ca_topic_score_gemma":0.005973822,"domain_scores_codex":[0.9997714,0.00002984553,0.00001188345,0.00008002144,0.00006817607,0.00003860984],"domain_scores_gemma":[0.9997576,0.00006072649,0.00002290313,0.00002369845,0.0001162375,0.00001894565],"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":[0.0008633346,0.001081739,0.008056973,0.0001388247,0.0001221568,0.0005479329,0.0001025063,0.109162,0.1164904,0.0006984395,0.007539141,0.7551966],"study_design_scores_gemma":[0.000009275615,0.0001170429,0.0013744,0.0000046483,0.00001488065,0.0000434878,0.000008813414,0.9871362,0.01076912,0.0001564535,0.0003568033,0.000008801981],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5724472,0.0007799611,0.4052803,0.0007367331,0.0004639252,0.0003555939,0.0003839043,0.01067036,0.008882018],"genre_scores_gemma":[0.9428116,0.0001167479,0.05201611,0.0001944146,0.0000477877,0.00007908256,0.0001879957,0.00003272488,0.004513524],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006634749,"threshold_uncertainty_score":0.01319224,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02495308289389219,"score_gpt":0.2878465697433188,"score_spread":0.2628934868494266,"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."}}