{"id":"W4229455392","doi":"10.3390/healthcare10050873","title":"Intelligent Real-Time Face-Mask Detection System with Hardware Acceleration for COVID-19 Mitigation","year":2022,"lang":"en","type":"article","venue":"Healthcare","topic":"Face recognition and analysis","field":"Computer Science","cited_by":28,"is_retracted":false,"has_abstract":true,"ca_institutions":"Lakehead University","funders":"","keywords":"Computer science; Computer hardware; Hardware acceleration; Acceleration; USB; Embedded system; Face detection; Artificial intelligence; Real-time computing; Facial recognition system; Pattern recognition (psychology); Operating system; Software; Field-programmable gate array","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":[0.0002852442,0.0006786592,0.0004028224,0.0004079381,0.000206792,0.0004401907,0.001357008,0.0003767449,0.006583987],"category_scores_gemma":[0.0007817503,0.0002384742,0.0002552343,0.0001503708,0.000176118,0.0007391083,0.0008019663,0.0004490587,0.001710733],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005657891,"about_ca_system_score_gemma":0.0007245871,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002314005,"about_ca_topic_score_gemma":0.003620746,"domain_scores_codex":[0.9997064,0.00002112487,0.00001047433,0.00006496297,0.0001530644,0.00004389721],"domain_scores_gemma":[0.9998106,0.00003271926,0.00001816551,0.00004017964,0.00007967528,0.00001877154],"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":[0.00125086,0.0002826319,0.005033099,0.0002662689,0.0001016664,0.0003895162,0.0001840559,0.02243988,0.2241893,0.00401663,0.02258635,0.7192599],"study_design_scores_gemma":[0.0001119868,0.0006270724,0.005355121,0.00003923063,0.00008682911,0.0007665642,0.00006618234,0.7302861,0.2349223,0.002046698,0.02561924,0.00007275929],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1339848,0.0006928554,0.8302987,0.0003698864,0.0003789943,0.000318834,0.0005423911,0.02460723,0.008806312],"genre_scores_gemma":[0.6718596,0.0002038971,0.3159381,0.0004318609,0.00004672129,0.0002296949,0.000871214,0.0004197244,0.009999208],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006583987,"threshold_uncertainty_score":0.02202564,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04119375223552211,"score_gpt":0.2996253539685414,"score_spread":0.2584316017330193,"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."}}