{"id":"W2909576138","doi":"10.1007/s00521-018-03996-8","title":"Adaptive sampling for UAV tracking","year":2019,"lang":"en","type":"article","venue":"Neural Computing and Applications","topic":"Video Surveillance and Tracking Methods","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Ottawa","funders":"National Natural Science Foundation of China","keywords":"Computational Science and Engineering; Computer science; Adaptive sampling; Tracking (education); Sampling (signal processing); Artificial intelligence; Computer vision; Machine learning; Mathematics; Statistics; Monte Carlo method; Psychology","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":[0.0003123086,0.00009222151,0.0001299087,0.00004265611,0.0002482004,0.0001351882,0.0002780561,0.00003339907,8.039108e-7],"category_scores_gemma":[0.0000168556,0.00008839634,0.0000477339,0.0001975668,0.00001811304,0.0001351645,0.00009172361,0.0001016645,0.00000975044],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000008786362,"about_ca_system_score_gemma":0.00001357527,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005282434,"about_ca_topic_score_gemma":0.000001046606,"domain_scores_codex":[0.9991808,0.00003250949,0.000150555,0.0003588362,0.00007731892,0.0002000091],"domain_scores_gemma":[0.9989608,0.0005705476,0.00007478515,0.0002753162,0.00007091762,0.00004762379],"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":[0.000003388758,0.00002064819,0.003607857,0.00002668527,0.000009509972,1.714833e-7,0.0002033547,0.002865189,0.00150943,0.09333409,0.00002815298,0.8983915],"study_design_scores_gemma":[0.0005693581,0.0001332516,0.03001268,0.0000400034,0.00000915353,0.0000280569,0.00007651595,0.930918,0.0009952415,0.02140393,0.01544207,0.0003717803],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.058482,0.0001282821,0.9399182,0.0003178394,0.0001155418,0.0003853252,0.000002331149,0.0001851534,0.0004653553],"genre_scores_gemma":[0.814866,0.000002915756,0.1847329,0.0002106562,0.0001222254,0.00002571083,0.000002367331,0.000006851763,0.00003041344],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9280528,"threshold_uncertainty_score":0.3604698,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06405725881614496,"score_gpt":0.3468457038133447,"score_spread":0.2827884449971998,"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."}}