{"id":"W3109489651","doi":"10.1109/ccece47787.2020.9255691","title":"Conditional Probabilistic Relative Visual Localization for Unmanned Aerial Vehicles","year":2020,"lang":"en","type":"article","venue":"","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Moncton","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; GNSS applications; Computer vision; Inertial measurement unit; Artificial intelligence; Simultaneous localization and mapping; Global Positioning System; Sensor fusion; Particle filter; Bundle adjustment; Feature extraction; Real-time computing; Mobile robot; Filter (signal processing); Photogrammetry; Robot","routes":{"ca_aff":true,"ca_fund":true,"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":[0.001331773,0.0005501248,0.0005034519,0.001011035,0.0002180293,0.0006995621,0.001067265,0.0004835413,0.0009803285],"category_scores_gemma":[0.005752458,0.0003057894,0.0005541515,0.0007997524,0.0006635003,0.001121688,0.001078459,0.0006005158,0.0002999722],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008127933,"about_ca_system_score_gemma":0.0005816438,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005575199,"about_ca_topic_score_gemma":0.004020087,"domain_scores_codex":[0.9989237,0.0003449236,0.00003881184,0.0002115996,0.0004155915,0.00006530652],"domain_scores_gemma":[0.9982594,0.0008330362,0.0003806772,0.0001602334,0.0003127187,0.00005389736],"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":[0.0001369435,0.00003659902,0.001434189,0.0001355798,0.00006201857,0.00006400947,0.00006100736,0.8579722,0.005837468,0.01439263,0.001146137,0.1187211],"study_design_scores_gemma":[0.000003448626,0.00003461158,0.0006596621,0.000006745639,0.000005900891,0.00002191828,0.000006016869,0.9949688,0.0008185009,0.003061682,0.0004044772,0.000008146197],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.007990212,0.0002312376,0.9909858,0.00005391379,0.00001720912,0.00001376484,0.00003406049,0.0002961571,0.0003777247],"genre_scores_gemma":[0.8093736,0.0005296028,0.1876127,0.00009064328,0.00007816085,0.0001099098,0.0004729927,0.00009532858,0.001636921],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005575199,"threshold_uncertainty_score":0.01108551,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01863773137352158,"score_gpt":0.2336807787261603,"score_spread":0.2150430473526387,"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."}}