{"id":"W2108194865","doi":"10.1109/crv.2012.55","title":"A Metaheuristic Bat-Inspired Algorithm for Full Body Human Pose Estimation","year":2012,"lang":"en","type":"article","venue":"","topic":"Video Surveillance and Tracking Methods","field":"Computer Science","cited_by":38,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Metaheuristic; Particle swarm optimization; Ant colony optimization algorithms; Firefly algorithm; Parallel metaheuristic; Computer science; Mathematical optimization; Optimization problem; Particle filter; Multi-swarm optimization; Population; Algorithm; Filter (signal processing); Artificial intelligence; Mathematics; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001239237,0.0001379384,0.0001994537,0.00009291419,0.0001883489,0.0001275795,0.0004065016,0.00005533937,0.00002382957],"category_scores_gemma":[0.0001242941,0.000118302,0.0000952018,0.000215702,0.00002119857,0.0007166601,0.00008398545,0.00006551782,0.00006464903],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002675612,"about_ca_system_score_gemma":0.00002337082,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002728835,"about_ca_topic_score_gemma":0.00000521139,"domain_scores_codex":[0.9988045,0.0001075785,0.0002408958,0.0002574878,0.0001897763,0.0003998319],"domain_scores_gemma":[0.9989946,0.0002494131,0.00008745259,0.000455442,0.00008851807,0.0001245169],"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":[0.000004099526,0.0002071668,0.0006499921,0.00002941369,0.00005152441,0.00000280765,0.0003280195,0.00004868655,0.002814245,0.07957906,0.001834543,0.9144505],"study_design_scores_gemma":[0.0008360627,0.0002783473,0.01674239,0.00001473144,0.00003420799,0.00003301694,0.00001024561,0.9489247,0.005956387,0.02011891,0.006617067,0.0004339435],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.002624985,0.0001155816,0.9940528,0.0001926468,0.0007265333,0.0002436241,0.000003533261,0.0003131785,0.00172708],"genre_scores_gemma":[0.2948802,0.000001238707,0.7044575,0.0001728255,0.0001471622,0.00003938398,0.000009458421,0.000009519387,0.0002826935],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.948876,"threshold_uncertainty_score":0.4824215,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03636191628798006,"score_gpt":0.3360088104941333,"score_spread":0.2996468942061532,"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."}}