{"id":"W2162269192","doi":"10.5539/cis.v5n3p110","title":"Survey on Gesture Recognition for Hand Image Postures","year":2012,"lang":"en","type":"article","venue":"Computer and Information Science","topic":"Hand Gesture Recognition Systems","field":"Computer Science","cited_by":81,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Gesture; Gesture recognition; Representation (politics); Human–computer interaction; Artificial intelligence; Context (archaeology); Computer vision; Selection (genetic algorithm); Object (grammar); Cognitive neuroscience of visual object recognition; Pattern recognition (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":[0.0006645176,0.001095015,0.001639509,0.00375276,0.0002952241,0.00130406,0.001281104,0.0009759101,0.005425852],"category_scores_gemma":[0.00165739,0.0004809448,0.001113936,0.004606095,0.0003479192,0.002296717,0.0004983394,0.0005472453,0.004865415],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000353015,"about_ca_system_score_gemma":0.0007506827,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002574208,"about_ca_topic_score_gemma":0.001856037,"domain_scores_codex":[0.9990569,0.0001143137,0.00014909,0.0003126246,0.000304128,0.00006292228],"domain_scores_gemma":[0.9991487,0.0003472198,0.00005865932,0.00008210028,0.0003377828,0.00002555169],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.00007550481,0.0000565984,0.0009747218,0.002755917,0.00008204181,0.0001167034,0.00007762438,0.001326492,0.007066534,0.001973594,0.008079645,0.9774145],"study_design_scores_gemma":[0.00005216531,0.0008434798,0.02495472,0.004243733,0.0007626486,0.005868914,0.0006224468,0.04333031,0.03888637,0.00922329,0.8709104,0.0003015041],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"review","genre_gemma":"empirical","genre_scores_codex":[0.01529189,0.6726049,0.2759251,0.0007787859,0.001292821,0.0002587819,0.0009078917,0.001931906,0.03100804],"genre_scores_gemma":[0.0946994,0.7090479,0.1517249,0.001264218,0.002063807,0.0003758511,0.003813734,0.0003233889,0.03668685],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005425852,"threshold_uncertainty_score":0.01815122,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03477949829373037,"score_gpt":0.276257173074662,"score_spread":0.2414776747809316,"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."}}