{"id":"W3159390462","doi":"10.1109/iccike51210.2021.9410789","title":"Batch Image Processing in Facial Detection Applications","year":2021,"lang":"en","type":"article","venue":"","topic":"Face and Expression Recognition","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Computer science; Artificial intelligence; Image processing; Computer vision; Batch processing; Face detection; Pattern recognition (psychology); Image (mathematics); Facial recognition system","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00005042024,0.00003700706,0.00004036631,0.000042493,0.00006657204,0.000107621,0.0001015193,0.00002879509,0.00004340336],"category_scores_gemma":[0.000009168046,0.00003512838,0.00001485138,0.0003719585,0.000006886645,0.0004226774,0.00005614118,0.00005632265,0.0001266996],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001413012,"about_ca_system_score_gemma":0.00004020479,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001296813,"about_ca_topic_score_gemma":0.00008086545,"domain_scores_codex":[0.9995545,0.00001682316,0.00008621757,0.0001750223,0.00007891369,0.00008852946],"domain_scores_gemma":[0.9997723,0.000007635998,0.00001714947,0.0001178527,0.00006149639,0.00002356412],"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":[6.72702e-7,0.00003762994,0.00007821029,0.000008597066,3.418937e-7,0.000003758554,0.0001344653,0.00000681164,0.1568161,0.0002655585,0.0001059037,0.8425419],"study_design_scores_gemma":[0.0004128614,0.00001462082,0.004230523,0.00003560654,0.000002178124,0.0000254832,0.0003375825,0.07100923,0.8901894,0.0104847,0.02302917,0.0002286053],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0120143,0.00002875302,0.9770021,0.0005273279,0.00004403933,0.00006630498,3.385271e-7,0.00009196487,0.01022482],"genre_scores_gemma":[0.9377324,0.000009221174,0.06135987,0.0002535725,0.0000358202,0.0000821249,0.000003484785,0.000002797101,0.0005207248],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9257181,"threshold_uncertainty_score":0.1628509,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01130670605940959,"score_gpt":0.2542571518686583,"score_spread":0.2429504458092487,"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."}}