{"id":"W3203658938","doi":"10.18280/ts.380404","title":"Comparison of the Effectiveness of Deep Learning Methods for Face Mask Detection","year":2021,"lang":"en","type":"article","venue":"Traitement du signal","topic":"Face recognition and analysis","field":"Computer Science","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Artificial intelligence; Convolutional neural network; Computer science; Deep learning; Transfer of learning; Face (sociological concept); Task (project management); Pattern recognition (psychology); Face detection; Computer vision; Facial recognition system; Engineering","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":[0.0009862686,0.00006755405,0.0002047118,0.00004551916,0.0000833325,0.00002173379,0.0001958935,0.0000291653,0.00003599531],"category_scores_gemma":[0.00008776215,0.00005271552,0.0001806521,0.0003671095,0.00002567288,0.00007765261,0.00006220955,0.00007196287,0.000001011229],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002047717,"about_ca_system_score_gemma":0.00002051342,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004596952,"about_ca_topic_score_gemma":0.000006829346,"domain_scores_codex":[0.9985811,0.0007839327,0.0002222106,0.0001651237,0.0001487714,0.00009883974],"domain_scores_gemma":[0.9989719,0.0005899444,0.0001407271,0.000123683,0.0001510322,0.00002268361],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00002322995,0.0001278542,0.001875021,0.0001437373,0.00009129853,1.502623e-7,0.0005269737,0.01442079,0.5544043,0.001011669,0.000001320007,0.4273737],"study_design_scores_gemma":[0.0002778401,0.00006650402,0.004725884,0.00002811553,0.00003271808,7.649365e-7,0.0001937389,0.3421098,0.6519949,0.0003677422,0.0001575507,0.00004444284],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06493083,0.0001111782,0.9345449,0.00004430563,0.00007947793,0.000137148,0.000001143397,0.00001683021,0.0001342041],"genre_scores_gemma":[0.9585507,0.000002537209,0.04137861,0.00001271986,0.000009062648,0.00002014297,0.000002251075,0.000003468891,0.00002053477],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8936198,"threshold_uncertainty_score":0.2149676,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03049594822451193,"score_gpt":0.3467342713199241,"score_spread":0.3162383230954122,"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."}}