{"id":"W3117881696","doi":"10.1109/iemcon51383.2020.9284856","title":"Detection of Long Narrow Landing Features for Autonomous UAV Perching","year":2020,"lang":"en","type":"article","venue":"","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ontario Tech University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"RANSAC; Point cloud; Computer science; Computer vision; Artificial intelligence; Position (finance); Perch; GRASP; Feature (linguistics); Line (geometry); Real-time computing; Mathematics","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":[0.0001855598,0.0003680019,0.0003044672,0.001008852,0.0002355869,0.000286798,0.0004297747,0.0003815175,0.0007934845],"category_scores_gemma":[0.0006102817,0.0002253336,0.0001983207,0.0004166685,0.0001643368,0.000336411,0.0004732902,0.00028546,0.0004866672],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001691744,"about_ca_system_score_gemma":0.0002742488,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001486046,"about_ca_topic_score_gemma":0.003082062,"domain_scores_codex":[0.9997776,0.00001981385,0.000006742621,0.00004494478,0.000111413,0.00003942417],"domain_scores_gemma":[0.9996316,0.00006392829,0.00005993732,0.00004690946,0.0001565533,0.00004097787],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003894988,0.0001499364,0.02215498,0.0001880175,0.00003732379,0.0009209195,0.0004011746,0.02446597,0.553838,0.0007937123,0.002171643,0.3944888],"study_design_scores_gemma":[0.00003790814,0.0004909518,0.06160493,0.00004609658,0.00003086448,0.001138139,0.0005060665,0.7688677,0.1626186,0.0007758854,0.003819359,0.00006350605],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4915336,0.0001991276,0.502412,0.00006985484,0.00004995591,0.0001301223,0.0001981577,0.002450085,0.002956938],"genre_scores_gemma":[0.8597171,0.00005602721,0.1391453,0.00002438491,0.000007684784,0.00004257673,0.0002211576,0.00005714543,0.0007285799],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001486046,"threshold_uncertainty_score":0.002954841,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01409414496828751,"score_gpt":0.210153823838638,"score_spread":0.1960596788703504,"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."}}