{"id":"W2556921987","doi":"","title":"ROBUST EXTRACTION OF TRAFFIC SIGNS FROM GEOREFERENCED MOBILE MAPPING IMAGES","year":2009,"lang":"en","type":"article","venue":"","topic":"Automated Road and Building Extraction","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"GNSS applications; Scale-invariant feature transform; Computer science; Georeference; Feature extraction; Global Positioning System; Computer vision; Matching (statistics); Data mining; Artificial intelligence; Real-time computing; Geography; Telecommunications","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":[0.00004689573,0.0001049862,0.0001306631,0.00008749651,0.00003084328,0.0000193044,0.00006327951,0.00009032006,0.0003289532],"category_scores_gemma":[0.000005230696,0.00009700153,0.00004460313,0.0001277888,0.000009587407,0.0002278499,0.000003230653,0.0001184238,0.0000284998],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000318955,"about_ca_system_score_gemma":0.000005360065,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002099904,"about_ca_topic_score_gemma":0.00000307449,"domain_scores_codex":[0.9994493,0.00000834801,0.000193667,0.0001180803,0.00009565411,0.0001349993],"domain_scores_gemma":[0.9997593,0.00003350962,0.00003778818,0.0001147223,0.00002305321,0.00003161833],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000002546882,0.00002698842,0.00001095473,0.000007326623,0.00001114079,9.2128e-7,0.00007550811,0.4430147,0.5106437,0.00001209596,0.001303069,0.04489107],"study_design_scores_gemma":[0.0005194812,0.0001749346,0.02740301,0.0001212084,0.000042085,0.00001155985,0.0007203466,0.6130845,0.3541172,0.0002133526,0.003102544,0.0004898676],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9449371,0.0001641868,0.0483882,0.00001603158,0.0002854485,0.0001003276,0.000007582292,0.0009167116,0.005184479],"genre_scores_gemma":[0.9941891,0.00007934287,0.005457507,0.000008410678,0.00009639232,0.000005200716,0.00002443862,0.00001152707,0.0001280519],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1700698,"threshold_uncertainty_score":0.3955608,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01923926775249274,"score_gpt":0.2250327713191596,"score_spread":0.2057935035666669,"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."}}