{"id":"W4404371600","doi":"10.1109/cyber63482.2024.10748903","title":"Visual SLAM Fusing Robust Segmentation of Moving Targets and NeRF","year":2024,"lang":"en","type":"article","venue":"","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Jiangsu Provincial Key Research and Development Program","keywords":"Computer vision; Artificial intelligence; Computer science; Segmentation; Image segmentation; Robustness (evolution); Biology","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":[0.00004144762,0.00005215675,0.0000554291,0.00006205248,0.00001718368,0.00003875482,0.00001197675,0.0000268523,0.00003283082],"category_scores_gemma":[0.000004191735,0.00004937956,0.00001254826,0.0000728471,0.000007966948,0.00008957468,0.000006295814,0.00003159401,0.000003995428],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001697507,"about_ca_system_score_gemma":0.000004507774,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001998737,"about_ca_topic_score_gemma":0.000007570381,"domain_scores_codex":[0.9996953,0.000005027698,0.0001053258,0.00006744493,0.00005991276,0.00006697479],"domain_scores_gemma":[0.9999125,0.00001888574,0.000005756734,0.00003021242,0.00001361087,0.0000190447],"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":[8.261019e-7,0.000003484822,0.0001656541,0.0001634835,0.00001358197,0.00000234789,0.0002261713,0.9255927,0.06426101,0.001266054,0.0001648728,0.008139778],"study_design_scores_gemma":[0.00005157931,0.000011393,0.0002427641,0.00003479384,0.000009091532,0.000001454764,0.00008092623,0.9661529,0.03322525,0.00004519548,0.00008840903,0.00005625469],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.274363,0.0005696701,0.7222798,0.00002609027,0.0002249178,0.00005608783,0.000001159435,0.0001615322,0.002317724],"genre_scores_gemma":[0.9923758,0.00006057673,0.007395901,0.00001109153,0.00003837066,8.015917e-7,0.00001205779,0.00001529251,0.00009012295],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7180128,"threshold_uncertainty_score":0.201364,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008657196594400623,"score_gpt":0.2204840324954982,"score_spread":0.2118268359010975,"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."}}