{"id":"W4399855192","doi":"10.18280/isi.290338","title":"Facial Expression Recognition Using Data Augmentation and Transfer Learning","year":2024,"lang":"en","type":"article","venue":"Ingénierie des systèmes d information","topic":"Face and Expression Recognition","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Facial expression recognition; Transfer of learning; Computer science; Facial expression; Artificial intelligence; Psychology; Pattern recognition (psychology); Speech recognition; Facial recognition system","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":[0.0004854262,0.000623563,0.0004863071,0.0006535278,0.0001985862,0.0004481212,0.0007686225,0.0003930737,0.002452951],"category_scores_gemma":[0.0008708971,0.0001975627,0.0008990669,0.0006128696,0.0003323748,0.0007572676,0.0006697614,0.0007545843,0.001181392],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003792397,"about_ca_system_score_gemma":0.0004308802,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002675486,"about_ca_topic_score_gemma":0.002557363,"domain_scores_codex":[0.9996339,0.00005455436,0.00001658007,0.000109618,0.0001266999,0.00005872252],"domain_scores_gemma":[0.9998158,0.00003559449,0.00001528534,0.00005561623,0.00006865114,0.000009184492],"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":[0.0001824211,0.0001711259,0.001469859,0.00006487549,0.00006723613,0.0001069416,0.00007513483,0.03657809,0.05385075,0.001678974,0.005155609,0.9005989],"study_design_scores_gemma":[0.0000126501,0.0001712328,0.003263087,0.00002376032,0.00003950523,0.0002251536,0.00006147321,0.9359452,0.05081298,0.003257925,0.006161352,0.00002568315],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1135993,0.00108105,0.8693765,0.0005566517,0.0003845578,0.0002021343,0.0005845588,0.004719218,0.009496035],"genre_scores_gemma":[0.7731053,0.0009165003,0.2115006,0.0003339389,0.0001188971,0.0002090555,0.001606449,0.000187998,0.01202128],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002675486,"threshold_uncertainty_score":0.008205891,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0508296584759465,"score_gpt":0.2767068796511565,"score_spread":0.22587722117521,"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."}}