{"id":"W4388877655","doi":"10.1063/5.0150392","title":"Deep learning-based vehicles tracking in traffic with image processing techniques","year":2023,"lang":"en","type":"article","venue":"AIP conference proceedings","topic":"Video Surveillance and Tracking Methods","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"Horizon College and Seminary","funders":"","keywords":"Computer science; Artificial intelligence; Computer vision; Deep learning; Image processing; Tracking (education); Image (mathematics)","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":[0.0004365536,0.0005676148,0.0005896259,0.0008822629,0.0002924722,0.0007244208,0.0008453191,0.0007881446,0.001084889],"category_scores_gemma":[0.001052779,0.0004326989,0.0005851263,0.001265768,0.0003438327,0.0008217214,0.0007289404,0.0009661332,0.0005250804],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005453374,"about_ca_system_score_gemma":0.0007964115,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01030082,"about_ca_topic_score_gemma":0.00996214,"domain_scores_codex":[0.9997887,0.00002815827,0.000007775278,0.00006302268,0.00004941709,0.00006288951],"domain_scores_gemma":[0.9997408,0.00008164805,0.00003466602,0.00002774464,0.00009226332,0.00002290122],"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":[0.000199653,0.0002198232,0.004621434,0.00007375189,0.00009888832,0.00006442387,0.00005911889,0.5179044,0.01602021,0.006092083,0.002819965,0.4518262],"study_design_scores_gemma":[0.000001443453,0.000008934002,0.0003482647,0.000002423182,0.00000446872,0.000005800152,0.000003010561,0.9977543,0.0009996532,0.0006893228,0.0001806524,0.000001891655],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.086553,0.0004696643,0.9093589,0.0001960692,0.00009031532,0.00002691863,0.0001618074,0.0006459998,0.002497355],"genre_scores_gemma":[0.8459381,0.0005092146,0.1465638,0.0001352714,0.00009599683,0.00004306386,0.0005027937,0.00007616886,0.00613565],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01030082,"threshold_uncertainty_score":0.02048171,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03009537120021491,"score_gpt":0.2973134512207737,"score_spread":0.2672180800205589,"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."}}