{"id":"W4312177448","doi":"10.18280/ria.360520","title":"Deep Neural Networks for Automatic Facial Expression Recognition","year":2022,"lang":"en","type":"article","venue":"Revue d intelligence artificielle","topic":"Face and Expression Recognition","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Artificial intelligence; Facial expression; Local binary patterns; Histogram; Classifier (UML); Deep learning; Pattern recognition (psychology); Facial recognition system; Facial expression recognition; Artificial neural network; Expression (computer science); Speech recognition; Image (mathematics)","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":[0.000421059,0.0001602964,0.0001766653,0.0001331288,0.0008920105,0.0001329722,0.0006845829,0.00005996089,0.0006077983],"category_scores_gemma":[0.00007991516,0.0001653409,0.0001482192,0.000445231,0.00003373991,0.0004162655,0.0003423236,0.0002357326,0.0001237814],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005773123,"about_ca_system_score_gemma":0.0000183732,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006086506,"about_ca_topic_score_gemma":0.000002174338,"domain_scores_codex":[0.9983222,0.000135853,0.0004172122,0.0004963388,0.0002349817,0.0003933904],"domain_scores_gemma":[0.9989775,0.0002346105,0.0001664294,0.0004324983,0.00009089171,0.00009806753],"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":[0.00002337347,0.0001366424,0.0000159594,0.00002893213,0.000004956994,0.000007022477,0.00108831,0.290516,0.003809545,0.0002987038,0.001957222,0.7021133],"study_design_scores_gemma":[0.00007345434,0.0001873205,0.000006525025,0.00002661597,0.000006156043,0.00002713946,0.0006004972,0.968096,0.02304125,0.004584659,0.003125856,0.0002245156],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02001118,0.0001648796,0.9768118,0.0005447216,0.001280865,0.0005386471,0.00001013435,0.0002601029,0.0003777283],"genre_scores_gemma":[0.9799398,0.0000154274,0.01832586,0.0004966774,0.000164471,0.0006514569,0.00008875972,0.0000198192,0.0002976934],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9599286,"threshold_uncertainty_score":0.6860714,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04658577910050946,"score_gpt":0.2696359850984988,"score_spread":0.2230502059979893,"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."}}