{"id":"W4404031975","doi":"10.1109/icccnt61001.2024.10725638","title":"Multimodal Emotion Recognition Using Computer Vision: A Comprehensive Approach","year":2024,"lang":"en","type":"article","venue":"","topic":"IoT-based Smart Home Systems","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Emotion recognition; Artificial intelligence; Computer vision; Human–computer interaction; Speech recognition","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0006482833,0.0009397375,0.0007810233,0.001865746,0.0002830639,0.001392741,0.0006599689,0.0009994892,0.001504038],"category_scores_gemma":[0.001135705,0.0003031109,0.0008641762,0.00111655,0.0003202757,0.001369162,0.0009392193,0.000967349,0.0009877426],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004203522,"about_ca_system_score_gemma":0.0004385118,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001402909,"about_ca_topic_score_gemma":0.001809142,"domain_scores_codex":[0.999467,0.00009334107,0.00002978976,0.0001527264,0.0002096672,0.0000474861],"domain_scores_gemma":[0.9996866,0.00004801866,0.00003362816,0.00004255386,0.0001659801,0.00002323293],"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":[0.00008959284,0.0001725397,0.001333317,0.000304015,0.0002119503,0.0001226975,0.00007484377,0.01595533,0.06403544,0.004988169,0.007268861,0.9054432],"study_design_scores_gemma":[0.00002156269,0.0003747728,0.0114349,0.0001901661,0.000253953,0.0007074516,0.0002396371,0.8802066,0.04895872,0.02465212,0.03285764,0.000102443],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01245807,0.007452071,0.9733062,0.0005868323,0.000182595,0.00009811296,0.0001669233,0.0007913862,0.004957701],"genre_scores_gemma":[0.4151986,0.01557856,0.5556726,0.0009258029,0.0007536931,0.0002574741,0.001193613,0.000242518,0.01017721],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001865746,"threshold_uncertainty_score":0.005031466,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02837219221057608,"score_gpt":0.2453677409923563,"score_spread":0.2169955487817802,"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."}}