{"id":"W2070584460","doi":"10.1109/icassp.2010.5495895","title":"Accelerometer-based gesture recognition via dynamic-time warping, affinity propagation, & compressive sensing","year":2010,"lang":"en","type":"article","venue":"","topic":"Hand Gesture Recognition Systems","field":"Computer Science","cited_by":114,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Gesture; Accelerometer; Dynamic time warping; Gesture recognition; Computer science; Speech recognition; Artificial intelligence; Compressed sensing; Acceleration; Pattern recognition (psychology); Computer vision","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":[0.000361296,0.00049341,0.0005290862,0.0003806937,0.0002356354,0.0004456171,0.0007178704,0.0004407483,0.001811169],"category_scores_gemma":[0.0013499,0.0002732211,0.0002355159,0.0006077515,0.0003955669,0.0007749844,0.0005771751,0.0004942078,0.001096483],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002004843,"about_ca_system_score_gemma":0.0003709223,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001828108,"about_ca_topic_score_gemma":0.003335162,"domain_scores_codex":[0.9995149,0.00007999314,0.00002663559,0.00009254285,0.0002529678,0.00003285749],"domain_scores_gemma":[0.9995895,0.0001392147,0.00006378858,0.00007301389,0.0001105924,0.00002397326],"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":[0.0002351894,0.0001350649,0.001216364,0.000122821,0.00004336466,0.0001312923,0.00009271663,0.03943835,0.1834761,0.00233669,0.002566833,0.7702051],"study_design_scores_gemma":[0.00003167037,0.0002437003,0.003215662,0.00001651925,0.00002286428,0.0005542166,0.00003248033,0.8760363,0.1134085,0.001892939,0.004491291,0.00005384722],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03272995,0.0002767044,0.9640115,0.0001403961,0.00005537256,0.00006020077,0.00007973282,0.001100988,0.001545133],"genre_scores_gemma":[0.3273032,0.0004407491,0.6662802,0.0001518624,0.00007808375,0.0001499755,0.000274453,0.00007207737,0.005249442],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001828108,"threshold_uncertainty_score":0.006058991,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02054902887433663,"score_gpt":0.249766980174545,"score_spread":0.2292179513002083,"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."}}