{"id":"W3157481245","doi":"10.1007/s10514-021-09979-4","title":"Semantic visual SLAM in dynamic environment","year":2021,"lang":"en","type":"article","venue":"Autonomous Robots","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":53,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Computer science; Reprojection error; Artificial intelligence; Simultaneous localization and mapping; Computer vision; RGB color model; Segmentation; Semantic mapping; Pixel; State (computer science); Image (mathematics); Robot; Algorithm; Mobile robot","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":[0.00004791229,0.0001264072,0.0001542235,0.00006726642,0.00002733768,0.00002820951,0.00005649575,0.00007543188,0.000145425],"category_scores_gemma":[0.000007319059,0.0001484498,0.00003949145,0.0000982389,0.00001389397,0.00005253624,0.00002427718,0.0001066618,0.0001873886],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000183302,"about_ca_system_score_gemma":0.00002541041,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001441788,"about_ca_topic_score_gemma":0.00005856843,"domain_scores_codex":[0.9992446,0.00002201067,0.0002147449,0.0001837943,0.0001001884,0.0002346102],"domain_scores_gemma":[0.9997304,0.00002021548,0.00001544894,0.0001764739,0.000008768257,0.00004870044],"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":[8.019829e-7,0.00004146397,0.0005597086,0.00002483512,0.00001145355,0.00008585325,0.0000980606,0.9897239,0.005659725,0.0002039357,0.00003128935,0.003558955],"study_design_scores_gemma":[0.0002411365,0.00001533586,0.00822183,0.00002058266,0.000007490921,0.00001139134,0.00002457531,0.9862949,0.003883113,0.0001644112,0.0009344274,0.0001807707],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5389343,0.001154287,0.4534756,0.0003279089,0.0006812021,0.0002563448,0.000004864798,0.0003742015,0.00479129],"genre_scores_gemma":[0.9964117,0.0001295203,0.002767642,0.00005831754,0.0000224796,0.000007564787,0.00005088077,0.00003746236,0.0005144217],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4574774,"threshold_uncertainty_score":0.6053607,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004858096576331655,"score_gpt":0.2014151424008672,"score_spread":0.1965570458245355,"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."}}