{"id":"W3141185698","doi":"10.1109/iccspa49915.2021.9385709","title":"Visual Heading Estimation for UAVs in Indoor Environments","year":2021,"lang":"en","type":"article","venue":"","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Drone; Computer science; Heading (navigation); Artificial intelligence; Real-time computing; Computer vision; Lidar; GNSS applications; Global Positioning System; Remote sensing; Engineering; Aerospace engineering; Geography","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":[0.0001426394,0.0004924238,0.0003248472,0.0005243849,0.000168981,0.0003637556,0.0002574349,0.0002639163,0.0008100815],"category_scores_gemma":[0.0006414687,0.000148746,0.0001882991,0.0003328301,0.0001198838,0.0002921511,0.0003036342,0.0002329214,0.0003946898],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001917587,"about_ca_system_score_gemma":0.0002337107,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0030682,"about_ca_topic_score_gemma":0.003106396,"domain_scores_codex":[0.9998571,0.00002983489,0.000004417279,0.00003614651,0.0000481605,0.00002433237],"domain_scores_gemma":[0.9997968,0.00004828471,0.00003403259,0.00002401526,0.00008306267,0.0000137301],"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":[0.000665427,0.0001011492,0.007679131,0.0003187588,0.00008698105,0.0003409165,0.0002961173,0.1373351,0.1629882,0.001270578,0.003062967,0.6858547],"study_design_scores_gemma":[0.00003704525,0.0004574604,0.01659707,0.00004780794,0.00004402598,0.0004362032,0.0003318502,0.9281594,0.04826143,0.001107054,0.004482942,0.0000376963],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2332464,0.001313218,0.7589669,0.0001181275,0.0001765029,0.00005202724,0.0001725496,0.002025746,0.003928578],"genre_scores_gemma":[0.900807,0.0004688326,0.0968012,0.00003150565,0.00004725905,0.00002110949,0.000247081,0.00003955577,0.001536444],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0030682,"threshold_uncertainty_score":0.006100714,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008374461359967495,"score_gpt":0.2318876095353371,"score_spread":0.2235131481753696,"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."}}