{"id":"W2091766585","doi":"10.1109/icme.2003.1220861","title":"Planar region depth filling using edge detection with embedded confidence technique and Hough transform","year":2003,"lang":"en","type":"article","venue":"","topic":"Image and Object Detection Techniques","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Computer vision; Hough transform; Artificial intelligence; Pixel; Planar; Coordinate system; Computer science; Enhanced Data Rates for GSM Evolution; Binary image; Boundary (topology); Edge detection; Projection (relational algebra); Depth map; Image (mathematics); Image processing; Mathematics; Computer graphics (images); Algorithm","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005912001,0.0006022258,0.0007723122,0.001365983,0.0002505009,0.0006363401,0.001388485,0.0008645621,0.001105988],"category_scores_gemma":[0.002273486,0.0006086848,0.0007611872,0.0009549145,0.0004461012,0.001949549,0.001019911,0.0007583354,0.0005259572],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002775749,"about_ca_system_score_gemma":0.0004736283,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000902841,"about_ca_topic_score_gemma":0.001044502,"domain_scores_codex":[0.9991466,0.00007434357,0.00003568493,0.00011236,0.0005732029,0.00005788293],"domain_scores_gemma":[0.9988887,0.0004165838,0.0001611819,0.0001746932,0.0003268402,0.00003198631],"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":[0.0003151479,0.0001014876,0.001590463,0.0002783333,0.00008160975,0.0002015825,0.0002525512,0.02960408,0.170628,0.005814151,0.001243385,0.7898892],"study_design_scores_gemma":[0.00005842712,0.0002878388,0.003094813,0.00002649174,0.00008964845,0.001534629,0.00009023498,0.7259359,0.2567134,0.004045886,0.008023733,0.00009896452],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01182661,0.000116095,0.9871896,0.00002526239,0.00001138707,0.00001424608,0.00001897767,0.0005321717,0.0002657462],"genre_scores_gemma":[0.1152387,0.0001765467,0.8835326,0.00002995804,0.00002544753,0.00002743241,0.0001169369,0.000113248,0.0007392042],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.001388485,"threshold_uncertainty_score":0.003699899,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01900751065808635,"score_gpt":0.240781627963859,"score_spread":0.2217741173057727,"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."}}