{"id":"W3094820928","doi":"10.18280/ts.370411","title":"A Facial Expression Recognition Model Based on Texture and Shape Features","year":2020,"lang":"en","type":"article","venue":"Traitement du signal","topic":"Face and Expression Recognition","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Artificial intelligence; Pattern recognition (psychology); Computer science; Support vector machine; Feature extraction; Classifier (UML); Computer vision; Facial expression; Facial recognition system; Three-dimensional face recognition; Convolutional neural network; Face detection","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001964445,0.0004472568,0.0003633955,0.0003352127,0.0001709834,0.0003819242,0.0005714774,0.0002976768,0.001420291],"category_scores_gemma":[0.0003322417,0.000189556,0.000659531,0.0003421993,0.0002237711,0.0005973661,0.0002292677,0.0004836519,0.0006659669],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003282755,"about_ca_system_score_gemma":0.0003103104,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004420076,"about_ca_topic_score_gemma":0.003068788,"domain_scores_codex":[0.999886,0.00001232914,0.000005209422,0.00004013614,0.00004239646,0.00001386489],"domain_scores_gemma":[0.9999547,0.000007831099,0.00000557398,0.000004880391,0.00002288649,0.000004154776],"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":[0.0003735836,0.0001682743,0.003839573,0.0001928765,0.0001461923,0.0004313824,0.0002363028,0.2879201,0.181484,0.01551036,0.006052034,0.5036454],"study_design_scores_gemma":[0.000005451045,0.00004444953,0.000987967,0.000004773923,0.00002557341,0.0001267664,0.00001049799,0.9922447,0.004319488,0.0009548143,0.001264987,0.00001050045],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03747448,0.0004395987,0.9548287,0.0002467892,0.0001360361,0.00007897144,0.0001584926,0.0007767792,0.005860329],"genre_scores_gemma":[0.8432257,0.001147332,0.1387888,0.0001608938,0.00009897276,0.0002228005,0.0004062553,0.0001068027,0.01584242],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004420076,"threshold_uncertainty_score":0.008788705,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03024614424429766,"score_gpt":0.2320205379838211,"score_spread":0.2017743937395235,"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."}}