{"id":"W2162576539","doi":"10.1109/cisda.2009.5356556","title":"Robust line extraction based on repeated segment directions on image contours","year":2009,"lang":"en","type":"article","venue":"","topic":"Image and Object Detection Techniques","field":"Computer Science","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Computer science; Computer vision; Artificial intelligence; Extraction (chemistry); Line (geometry); Image (mathematics); Image segmentation; Feature extraction; Line segment; Pattern recognition (psychology); Mathematics; Geometry","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":[0.00064159,0.001182703,0.0009814295,0.002761274,0.0003680873,0.001224728,0.00136664,0.00098221,0.003583395],"category_scores_gemma":[0.002115444,0.0008071504,0.001031104,0.001876832,0.0005534128,0.002338883,0.0007944483,0.0009271296,0.004163224],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003535486,"about_ca_system_score_gemma":0.0003654161,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007266371,"about_ca_topic_score_gemma":0.0008164693,"domain_scores_codex":[0.9990956,0.00009738093,0.000049846,0.000248127,0.0004417466,0.00006733881],"domain_scores_gemma":[0.9988306,0.0002769142,0.0001843976,0.0002138994,0.0004553211,0.00003875349],"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":[0.0003143462,0.00007151846,0.001010915,0.0002230256,0.00007238731,0.0002060116,0.0001331121,0.01246225,0.2228159,0.004121082,0.003144942,0.7554246],"study_design_scores_gemma":[0.00009141223,0.0003400583,0.006092344,0.00007955851,0.0001452092,0.00128643,0.0001242348,0.6076247,0.3424297,0.007271207,0.03433914,0.0001761299],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01033823,0.0002130977,0.9857803,0.00004705328,0.00003501484,0.00006882943,0.0000690298,0.002537014,0.000911442],"genre_scores_gemma":[0.05277494,0.0003270996,0.9440562,0.00004215377,0.00004602098,0.00008463868,0.0004144273,0.0004540542,0.001800461],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003583395,"threshold_uncertainty_score":0.01198769,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01824802882396509,"score_gpt":0.2678288569142102,"score_spread":0.2495808280902451,"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."}}