{"id":"W3206041734","doi":"10.3390/pr9101786","title":"Efficient Video-based Vehicle Queue Length Estimation using Computer Vision and Deep Learning for an Urban Traffic Scenario","year":2021,"lang":"en","type":"article","venue":"Processes","topic":"Autonomous Vehicle Technology and Safety","field":"Engineering","cited_by":31,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Queue; Real-time computing; Computer science; Simulation; Computer vision; Artificial intelligence; Computer network","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":[0.0002224567,0.0006080035,0.0003173626,0.0005612567,0.0001610274,0.0003461442,0.0007257783,0.0004357257,0.000726858],"category_scores_gemma":[0.0005704677,0.0002440289,0.0003506583,0.0004621813,0.0001248799,0.0005250401,0.0003126823,0.0005765807,0.0002653327],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008513823,"about_ca_system_score_gemma":0.0006295086,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02365912,"about_ca_topic_score_gemma":0.02534608,"domain_scores_codex":[0.9998896,0.000007815831,0.000004697509,0.00002838212,0.00003120542,0.00003835621],"domain_scores_gemma":[0.9998749,0.00002547484,0.00001824553,0.000007819788,0.00006001283,0.00001357322],"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":[0.0004092412,0.0003297426,0.008672288,0.0001232479,0.0001115105,0.0002226385,0.00005399865,0.6387243,0.03009065,0.001895484,0.003682223,0.3156846],"study_design_scores_gemma":[0.000002028321,0.00001284048,0.0005406464,0.000001282442,0.000003415229,0.000006001585,0.000003309671,0.9981565,0.00105172,0.0001522987,0.00006778266,0.000002163011],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2913741,0.0009172864,0.7017366,0.0002581703,0.000133034,0.0000655086,0.0004810417,0.002031796,0.003002503],"genre_scores_gemma":[0.9453012,0.0002401791,0.0520508,0.000062689,0.00003227474,0.00002494584,0.0006436383,0.0000394403,0.001604765],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02365912,"threshold_uncertainty_score":0.04704279,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01056465997462269,"score_gpt":0.2382315592492806,"score_spread":0.2276668992746579,"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."}}