{"id":"W4238847059","doi":"10.32920/ryerson.14648964","title":"Multimodal Information Fusion for Human Action Recognition","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Human Pose and Action Recognition","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Artificial intelligence; Computer science; Discriminative model; Pattern recognition (psychology); Representation (politics); Pooling; Locality; RGB color model; Canonical correlation; Modalities; Deep learning; Feature learning; Machine learning","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001069211,0.001109242,0.001051658,0.001549888,0.0003135396,0.001115261,0.001011521,0.0009013896,0.007572817],"category_scores_gemma":[0.00173859,0.0002774786,0.001176166,0.001493235,0.0006994878,0.002054694,0.001583969,0.001253362,0.002028264],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001151534,"about_ca_system_score_gemma":0.0007114524,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00428489,"about_ca_topic_score_gemma":0.004343485,"domain_scores_codex":[0.9991904,0.0001522301,0.00003443782,0.0002540963,0.0002666693,0.0001021597],"domain_scores_gemma":[0.9996306,0.00008790952,0.00005039878,0.00009545173,0.0001110319,0.0000246281],"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":[0.0002651565,0.0001246164,0.0007436349,0.0001990652,0.0001595636,0.0001207777,0.0001102045,0.05971272,0.02652431,0.01368244,0.01217586,0.8861818],"study_design_scores_gemma":[0.00001453624,0.0002225305,0.002811959,0.0000933173,0.0001087855,0.000212336,0.0001061546,0.914863,0.03061486,0.03468106,0.01620004,0.00007134805],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01423274,0.004691107,0.9688457,0.0005361575,0.0002204383,0.00008949066,0.000546097,0.003233137,0.007605129],"genre_scores_gemma":[0.6255758,0.004729164,0.3523862,0.0007628142,0.0004531888,0.0002084075,0.00237917,0.000343797,0.01316156],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007572817,"threshold_uncertainty_score":0.02533364,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07079110847569632,"score_gpt":0.3124610884846966,"score_spread":0.2416699800090003,"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."}}