{"id":"W4221126731","doi":"10.18280/ts.390111","title":"Comparative Analysis of OpenPose, PoseNet, and MoveNet Models for Pose Estimation in Mobile Devices","year":2022,"lang":"en","type":"article","venue":"Traitement du signal","topic":"Human Pose and Action Recognition","field":"Computer Science","cited_by":93,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Thunder; Estimation; Mobile device; Artificial intelligence; Data mining; Geography; Meteorology; Engineering","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":[0.001854456,0.001563229,0.0009152218,0.001487646,0.0003267789,0.0009622945,0.0009149619,0.000709757,0.002613798],"category_scores_gemma":[0.005359207,0.0003271449,0.0008764972,0.0007999319,0.0002933418,0.00159776,0.0006430856,0.0007592848,0.0008498548],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007016921,"about_ca_system_score_gemma":0.0006774179,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01590317,"about_ca_topic_score_gemma":0.0135712,"domain_scores_codex":[0.9989312,0.0002818175,0.00008246437,0.0002259367,0.0003528579,0.0001256247],"domain_scores_gemma":[0.9976711,0.001420042,0.0001338911,0.0002026057,0.0004927696,0.00007965101],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001384694,0.0003364306,0.01136953,0.0003997358,0.0002906937,0.0002446096,0.0001869588,0.4818267,0.01002532,0.00284613,0.00394129,0.487148],"study_design_scores_gemma":[0.00001394581,0.0003049482,0.003224286,0.00001802199,0.00004877729,0.0001116237,0.00006007839,0.9908618,0.003877004,0.0004311884,0.001026098,0.00002224502],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4011357,0.004272383,0.5790996,0.000482533,0.0005183759,0.0002531514,0.0009482976,0.005778641,0.007511352],"genre_scores_gemma":[0.9096639,0.001983784,0.08078934,0.0001302165,0.00007840228,0.0001508011,0.002593311,0.0002493162,0.004361015],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01590317,"threshold_uncertainty_score":0.03162122,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03830777199868675,"score_gpt":0.2962747317575524,"score_spread":0.2579669597588656,"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."}}