{"id":"W4406247558","doi":"10.18280/ts.410630","title":"Improved Intelligent Learning Filter in Deep Learning Systems and Its Application in Traffic Object Detection","year":2024,"lang":"en","type":"article","venue":"Traitement du signal","topic":"Traffic Prediction and Management Techniques","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Computer science; Artificial intelligence; Filter (signal processing); Object (grammar); Deep learning; Computer vision; Object detection; Real-time computing; Pattern recognition (psychology)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001091102,0.0004777145,0.0006962752,0.0006427679,0.0003987451,0.0007171288,0.000789326,0.001124891,0.001507192],"category_scores_gemma":[0.002399334,0.0002821597,0.0004965882,0.0007482465,0.0003497479,0.00104174,0.000571936,0.001043181,0.0004250924],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006534344,"about_ca_system_score_gemma":0.0009563946,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007618242,"about_ca_topic_score_gemma":0.006526059,"domain_scores_codex":[0.9996161,0.00007393043,0.00002080729,0.0001041285,0.0001266809,0.00005828429],"domain_scores_gemma":[0.9990243,0.0003855193,0.00006021563,0.00008608874,0.0004107334,0.00003314581],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003298086,0.000233715,0.002961223,0.0001620851,0.0001417125,0.0001053877,0.0001034729,0.3975639,0.03017693,0.01917426,0.004794412,0.5442531],"study_design_scores_gemma":[0.000002099462,0.00001584208,0.0002424785,0.000002404548,0.0000076516,0.00001089436,0.00000185138,0.9966431,0.001980775,0.0007183531,0.000371336,0.00000333053],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02021026,0.0006711138,0.9774596,0.0001591462,0.00009745963,0.00001400125,0.00004608279,0.0004730935,0.0008692837],"genre_scores_gemma":[0.5916898,0.0009558107,0.3967217,0.000222037,0.0001801352,0.00006932736,0.0002931235,0.0001260029,0.009742144],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007618242,"threshold_uncertainty_score":0.01514781,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007785130655865002,"score_gpt":0.2095312828185391,"score_spread":0.2017461521626741,"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."}}