{"id":"W4311165016","doi":"10.18280/ts.390536","title":"Threshold Values of Different Classical Edge Detection Algorithms","year":2022,"lang":"en","type":"article","venue":"Traitement du signal","topic":"Industrial Vision Systems and Defect Detection","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Prewitt operator; Sobel operator; Digital image; Edge detection; Canny edge detector; Algorithm; Threshold limit value; Image (mathematics); Mathematics; Enhanced Data Rates for GSM Evolution; Range (aeronautics); Computer science; Noise (video); Artificial intelligence; Image processing; 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":[0.002541654,0.001040438,0.0008403935,0.004591422,0.0006160828,0.001784433,0.001381615,0.001475327,0.002435684],"category_scores_gemma":[0.01260983,0.0003804468,0.0008268862,0.00373953,0.0005822423,0.001809679,0.0006016592,0.0006080215,0.00105265],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001130662,"about_ca_system_score_gemma":0.0005368638,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001429476,"about_ca_topic_score_gemma":0.001033908,"domain_scores_codex":[0.9968768,0.0004062471,0.0004629048,0.0005947081,0.00140377,0.0002554632],"domain_scores_gemma":[0.9941493,0.002176799,0.0003632599,0.0005274757,0.002643177,0.0001400561],"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":[0.002533939,0.0003736244,0.01082321,0.001724806,0.0003237442,0.000387211,0.0006308018,0.04597744,0.1224293,0.009096054,0.005428916,0.8002709],"study_design_scores_gemma":[0.0002231176,0.002010803,0.03682248,0.0004360288,0.000627027,0.002148448,0.0007857517,0.395576,0.5263012,0.0106233,0.02398138,0.0004645113],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.377103,0.01019394,0.5880433,0.0004007218,0.0007193681,0.0004319381,0.001237167,0.005385199,0.01648547],"genre_scores_gemma":[0.6451175,0.002157994,0.346,0.0001546155,0.00007148811,0.0003000099,0.001748637,0.000555551,0.00389436],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004591422,"threshold_uncertainty_score":0.01344168,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02240242423770257,"score_gpt":0.2254854954882277,"score_spread":0.2030830712505252,"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."}}