{"id":"W3216808814","doi":"10.18280/ts.380526","title":"Road Identification Through Efficient Edge Segmentation Based on Morphological Operations","year":2021,"lang":"en","type":"article","venue":"Traitement du signal","topic":"Automated Road and Building Extraction","field":"Engineering","cited_by":60,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Identification (biology); Computer science; Segmentation; Enhanced Data Rates for GSM Evolution; Computer vision; Artificial intelligence; Satellite; Edge detection; Image segmentation; Remote sensing; Satellite imagery; Data mining; Image processing; Image (mathematics); Geography; Engineering","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001056744,0.0001254744,0.00009494549,0.00005071054,0.0001407386,0.00008915296,0.00006088983,0.00006650601,0.0007365571],"category_scores_gemma":[0.00001081367,0.0001199852,0.00005587802,0.0001922286,0.00001649348,0.0001155897,0.00000695265,0.0001096396,0.0001363672],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001235753,"about_ca_system_score_gemma":0.00002051626,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004301586,"about_ca_topic_score_gemma":0.000003044914,"domain_scores_codex":[0.9990894,0.0000452876,0.0002585152,0.0002085874,0.0002415197,0.0001567185],"domain_scores_gemma":[0.9997305,0.00002481277,0.00002421581,0.0001296693,0.00005474471,0.00003605889],"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":[0.000005612883,0.0001520957,0.00002289551,0.00001295022,0.00001210339,0.00001733525,0.0001011367,0.6989115,0.2952339,0.0002421389,0.0007964518,0.004491776],"study_design_scores_gemma":[0.0004203564,0.0000386227,0.006815542,0.00002328329,0.00002332744,0.00001158113,0.00008375158,0.8176984,0.1741649,0.00001541833,0.0005683536,0.0001364607],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6593493,0.0000615842,0.337525,0.0002804178,0.0004614214,0.0002128978,0.00001936423,0.0004565979,0.001633515],"genre_scores_gemma":[0.996921,0.00001103133,0.00236601,0.0001512395,0.000116884,0.00006308877,0.0002923411,0.00001700515,0.0000614271],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3375717,"threshold_uncertainty_score":0.8064783,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01874237372211033,"score_gpt":0.2530750905238291,"score_spread":0.2343327168017188,"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."}}