{"id":"W3161500803","doi":"10.18280/ts.380233","title":"Dance Action Recognition and Pose Estimation Based on Deep Convolutional Neural Network","year":2021,"lang":"en","type":"article","venue":"Traitement du signal","topic":"Human Pose and Action Recognition","field":"Computer Science","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Convolutional neural network; Computer science; Artificial intelligence; Action (physics); Dance; Deep learning; Segmentation; Pose; Task (project management); Machine learning; Staring; Frame (networking); Sequence (biology); Pattern recognition (psychology); Engineering; Communication; Psychology","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":[0.0002091777,0.0008003959,0.0004981423,0.0005916545,0.0001829961,0.0003625508,0.0006262927,0.0004333589,0.001451488],"category_scores_gemma":[0.0004734967,0.0003112247,0.0004521089,0.0004115771,0.0002666525,0.0004665438,0.0004317019,0.0005809737,0.0004133134],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005307475,"about_ca_system_score_gemma":0.00054345,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01530727,"about_ca_topic_score_gemma":0.0212348,"domain_scores_codex":[0.9997984,0.00001956781,0.00001146149,0.00008069408,0.00005294102,0.00003699966],"domain_scores_gemma":[0.9998975,0.00001976628,0.00001539182,0.00001656898,0.00003707443,0.00001373817],"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":[0.0002449073,0.0001467201,0.004474348,0.00007364188,0.0001090042,0.0001852328,0.00006215496,0.2166644,0.05014918,0.00273344,0.003224074,0.7219329],"study_design_scores_gemma":[0.000003438804,0.0000309717,0.001519203,0.000004595049,0.00001289623,0.00003600175,0.000008042751,0.9913537,0.005751681,0.0007178687,0.0005536925,0.000007893585],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09163762,0.00087346,0.8998389,0.0001945504,0.0001513492,0.00005736855,0.0002829313,0.002436313,0.004527486],"genre_scores_gemma":[0.8633931,0.0008144396,0.1239956,0.0001733006,0.00007929197,0.00005659273,0.0008745457,0.00006943911,0.01054381],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01530727,"threshold_uncertainty_score":0.03043634,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04399115618748527,"score_gpt":0.252056106994896,"score_spread":0.2080649508074107,"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."}}