{"id":"W4382567607","doi":"10.2139/ssrn.4495229","title":"Smartface: A Multi-Threaded Face Recognition Framework for Edgetpu Devices and Efficient Model Training","year":2023,"lang":"en","type":"preprint","venue":"SSRN Electronic Journal","topic":"Face recognition and analysis","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Regina","funders":"","keywords":"Computer science; Training (meteorology); Facial recognition system; Face (sociological concept); Machine learning; Artificial intelligence; Speech recognition; Human–computer interaction; Pattern recognition (psychology); Sociology","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":[0.0005104401,0.001074348,0.001080187,0.0004773297,0.0004598388,0.001212992,0.002993659,0.00118313,0.01360916],"category_scores_gemma":[0.001459646,0.0006948625,0.0009091374,0.0004687137,0.0003503466,0.001982203,0.002060636,0.001581708,0.005029922],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00044579,"about_ca_system_score_gemma":0.0007337225,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003261989,"about_ca_topic_score_gemma":0.005004559,"domain_scores_codex":[0.9995259,0.0000532875,0.00002179091,0.0001304592,0.0001932523,0.00007526884],"domain_scores_gemma":[0.9996521,0.00007680424,0.00002393796,0.0001362386,0.00007799937,0.00003277994],"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":[0.0008934423,0.0002298146,0.001370037,0.0002331453,0.0001392015,0.0002954845,0.0001795203,0.08016603,0.05471709,0.009685253,0.04374866,0.8083424],"study_design_scores_gemma":[0.00002203124,0.00005969571,0.0002668394,0.00001071064,0.00001208198,0.00009590336,0.0000194069,0.9708246,0.0175461,0.005125313,0.005996545,0.00002080125],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.004627753,0.0001250038,0.9736513,0.00005184868,0.00005885836,0.00005184898,0.0001906127,0.02023702,0.001005718],"genre_scores_gemma":[0.1871175,0.0001762513,0.8012682,0.0002073504,0.00006223023,0.0002902699,0.001150713,0.002256791,0.007470747],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01360916,"threshold_uncertainty_score":0.04552722,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1024610061697151,"score_gpt":0.320405982800226,"score_spread":0.2179449766305109,"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."}}