{"id":"W4392355230","doi":"10.18280/ria.380102","title":"An Optimized Deep LSTM Model for Human Action Recognition","year":2024,"lang":"fr","type":"article","venue":"Revue d intelligence artificielle","topic":"Human Pose and Action Recognition","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Action recognition; Computer science; Artificial intelligence; Action (physics); Deep learning; Speech recognition; Pattern recognition (psychology); Physics","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":["metaepi_narrow","scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0008319825,0.0003488589,0.0003077904,0.0003475874,0.0006465662,0.001271999,0.0004971683,0.0003121713,0.001114303],"category_scores_gemma":[0.00006122547,0.0004092137,0.0003415064,0.0006270989,0.0001408974,0.002596255,0.00006214344,0.0004227247,0.002413551],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001960576,"about_ca_system_score_gemma":0.0001347816,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006475081,"about_ca_topic_score_gemma":0.0000968787,"domain_scores_codex":[0.9971457,0.0001544417,0.0007697074,0.00106765,0.0002356512,0.0006268293],"domain_scores_gemma":[0.9983555,0.0002284741,0.0001534908,0.0006194441,0.0003970703,0.0002459918],"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":[0.00002699467,0.0003849964,4.831487e-7,0.0005237499,0.00004741865,0.00002023113,0.00389278,0.1756282,0.00816501,0.04068374,0.001666035,0.7689604],"study_design_scores_gemma":[0.00007281369,0.0003083369,6.396471e-7,0.0005145532,0.00008819025,0.00006510411,0.0004239895,0.8250627,0.04988703,0.1121779,0.0109711,0.00042772],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.006821244,0.002147786,0.9810817,0.002207125,0.004090936,0.0007931317,0.00007466731,0.0005068828,0.002276505],"genre_scores_gemma":[0.8811057,0.001309233,0.07088463,0.0005502581,0.002199193,0.0004113924,0.0004512982,0.0001181079,0.0429702],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9101971,"threshold_uncertainty_score":0.999836,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1881254124429252,"score_gpt":0.3617840781402951,"score_spread":0.1736586656973698,"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."}}