{"id":"W4290079687","doi":"10.1155/2022/9328398","title":"Vision-Based Branch Road Detection for Intersection Navigation in Unstructured Environment Using Multi-Task Network","year":2022,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Autonomous Vehicle Technology and Safety","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Intersection (aeronautics); Computer science; Artificial intelligence; Task (project management); Minimum bounding box; Computer vision; Bounding overwatch; Occupancy grid mapping; Artificial neural network; Deep learning; Noise (video); Grid; Object detection; Pattern recognition (psychology); Transport engineering; Image (mathematics); Engineering; Mobile robot; Geography","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":[0.0001863746,0.0007043734,0.0005162698,0.0008000889,0.0003836681,0.0004297741,0.000974786,0.0006338064,0.001188901],"category_scores_gemma":[0.0006684704,0.0003462015,0.0004682948,0.0005908692,0.0002916307,0.0009769668,0.0008014006,0.0006550545,0.0003377206],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006468774,"about_ca_system_score_gemma":0.0009303293,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01156965,"about_ca_topic_score_gemma":0.01412897,"domain_scores_codex":[0.9997723,0.00002249512,0.000008446568,0.00007458797,0.00005988661,0.0000623509],"domain_scores_gemma":[0.9997844,0.00004824277,0.00003444239,0.00002648533,0.00008373545,0.00002264225],"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":[0.0004108781,0.0003348616,0.008663866,0.0001037337,0.0000925202,0.000224806,0.0001399181,0.4624325,0.02335677,0.002322505,0.004921154,0.4969965],"study_design_scores_gemma":[0.000004537691,0.00002779087,0.0009296818,0.000003121438,0.000007064651,0.00002030468,0.00001735071,0.9950143,0.002814393,0.0008428825,0.0003128466,0.000005634048],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1464051,0.0003228928,0.8471228,0.000218283,0.00009780654,0.00006117163,0.0002854758,0.00221151,0.003274994],"genre_scores_gemma":[0.9140682,0.0001463549,0.083069,0.00008192824,0.00002551746,0.00005624347,0.0005714865,0.00005077773,0.001930573],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01156965,"threshold_uncertainty_score":0.02300459,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00559821021398333,"score_gpt":0.2219454218347125,"score_spread":0.2163472116207292,"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."}}