{"id":"W3106974175","doi":"10.18280/ria.340501","title":"Novel Descriptors for Effective Recognition of Face and Facial Expressions","year":2020,"lang":"en","type":"article","venue":"Revue d intelligence artificielle","topic":"Face and Expression Recognition","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Artificial intelligence; Pattern recognition (psychology); Computer science; Facial recognition system; Support vector machine; Histogram; Histogram of oriented gradients; Facial expression; Classifier (UML); Three-dimensional face recognition; Face (sociological concept); Feature (linguistics); Computer vision; Face detection; 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":[0.0001444538,0.0001167353,0.000176733,0.00005707283,0.0001262001,0.00004655715,0.0002554985,0.00007221056,0.00002995898],"category_scores_gemma":[0.0002924835,0.0001101437,0.00007580192,0.0002522962,0.00005821706,0.0003312299,0.0001187154,0.00009264817,0.00004461565],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000009604727,"about_ca_system_score_gemma":0.00001729871,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001132868,"about_ca_topic_score_gemma":0.000001419449,"domain_scores_codex":[0.9990347,0.00003232307,0.0002781291,0.000370942,0.000103427,0.0001804841],"domain_scores_gemma":[0.9992232,0.0002430528,0.0001160365,0.0001697086,0.0001276872,0.000120326],"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":[0.00005567632,0.0001074315,0.00003859877,0.0001356191,0.00001285922,9.409469e-7,0.00603062,0.001266503,0.613319,0.0009236727,0.0007756971,0.3773334],"study_design_scores_gemma":[0.0001024971,0.0002494573,0.00003635284,0.0001329948,0.000009066332,0.000004067429,0.0008621079,0.2536281,0.7404339,0.001702778,0.002687526,0.0001511948],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06282772,0.00008969464,0.9350302,0.0009494186,0.0001898069,0.0005394296,0.00003912145,0.00006445719,0.0002701609],"genre_scores_gemma":[0.9629393,0.00004196127,0.03651335,0.0002563957,0.00006295891,0.0001061402,0.00001249828,0.000009436306,0.00005797171],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9001116,"threshold_uncertainty_score":0.4491528,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07607479668900234,"score_gpt":0.2782867029655383,"score_spread":0.2022119062765359,"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."}}