{"id":"W4386919837","doi":"10.1109/sas58821.2023.10254004","title":"Combined Radar and Camera Drone Detection in Urban Environment: A Simulation-Based Approach","year":2023,"lang":"en","type":"article","venue":"","topic":"UAV Applications and Optimization","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Defence Research and Development Canada; National Research Council Canada","funders":"","keywords":"Drone; Computer science; Radar; Remote sensing; Computer vision; Radar lock-on; Urban environment; Artificial intelligence; Radar imaging; Radar engineering details; Real-time computing; Environmental science; Geography; Telecommunications","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":[0.0004882721,0.000843389,0.0009281686,0.0009796727,0.0005051416,0.001188925,0.001155114,0.001789279,0.0027699],"category_scores_gemma":[0.001498238,0.0005579434,0.0009245269,0.000721362,0.0006138521,0.0006469739,0.0008986249,0.0008885057,0.0001887627],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008748302,"about_ca_system_score_gemma":0.001058032,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0319178,"about_ca_topic_score_gemma":0.02004025,"domain_scores_codex":[0.9997633,0.00008606439,0.00001016965,0.00003272485,0.00004620502,0.00006150886],"domain_scores_gemma":[0.9986957,0.0008719068,0.0001142872,0.00004825325,0.0001750443,0.0000948832],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001921272,0.00002250171,0.0005227503,0.000009982494,0.000008589624,0.00002052608,0.000007522703,0.9981626,0.0001232637,0.0004755329,0.0000504107,0.0005770875],"study_design_scores_gemma":[0.00000403357,0.000007904234,0.00007173421,0.000001697603,0.000002875864,0.00000276805,0.000008510849,0.9996508,0.00005579207,0.0001174355,0.00007436506,0.000001943566],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6586596,0.0009254665,0.3036724,0.001008848,0.0001339443,0.0002835013,0.0009849961,0.000803686,0.03352757],"genre_scores_gemma":[0.9679004,0.0003163261,0.02884285,0.00007686966,0.00002397892,0.0001150329,0.0002890057,0.00004407944,0.002391443],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0319178,"threshold_uncertainty_score":0.06346405,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006466458385268489,"score_gpt":0.1791935060085553,"score_spread":0.1727270476232868,"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."}}