{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003478422,0.000633952,0.0004850867,0.002139166,0.0003630041,0.0009071667,0.0006445432,0.0006119445,0.001355915],"category_scores_gemma":[0.0008459311,0.0003766557,0.0007321586,0.00111946,0.0004598982,0.001598552,0.0005362651,0.0005053229,0.001055068],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002139659,"about_ca_system_score_gemma":0.0004643192,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001014144,"about_ca_topic_score_gemma":0.001611452,"domain_scores_codex":[0.9995964,0.00004211093,0.00003546457,0.0001258847,0.0001523554,0.00004772372],"domain_scores_gemma":[0.9995151,0.0001187587,0.00008727798,0.00009424436,0.0001639687,0.0000207887],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0002213355,0.0001352059,0.002371066,0.0002772026,0.00006919084,0.0003573426,0.0002862118,0.025119,0.4205099,0.004858367,0.001414599,0.5443805],"study_design_scores_gemma":[0.00003026085,0.0003655643,0.01025046,0.00004529298,0.0001313573,0.001482077,0.0003041382,0.6291182,0.3418945,0.004377278,0.01190411,0.00009672431],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05328114,0.0001640611,0.9435878,0.00005471451,0.00003210484,0.00006844625,0.00005984564,0.0009840641,0.001767744],"genre_scores_gemma":[0.2692105,0.0003255335,0.7274721,0.00004622964,0.00002916184,0.00005882534,0.000256484,0.0001464617,0.002454596],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002139166,"threshold_uncertainty_score":0.004535973,"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."}}