{"id":"W2161953739","doi":"10.1109/icdar.1993.395730","title":"Evaluation of thinning algorithms from an OCR viewpoint","year":2002,"lang":"en","type":"article","venue":"","topic":"Digital Image Processing Techniques","field":"Computer Science","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Algorithm; Thinning; Social connectedness; Perspective (graphical); Artificial intelligence; Range (aeronautics); Character (mathematics); Noise (video); Process (computing); Parallel algorithm; Machine learning; Mathematics; Image (mathematics); Programming language; Engineering","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008337729,0.0000707596,0.00009359349,0.00005963801,0.00002808148,0.0001960438,0.0005930505,0.00002855743,0.0001189273],"category_scores_gemma":[0.0001009377,0.0000612505,0.00002477146,0.0001975993,0.0000278433,0.001895453,0.0001468439,0.0000482453,0.00002986231],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002953601,"about_ca_system_score_gemma":0.00002283892,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006053454,"about_ca_topic_score_gemma":0.000002559283,"domain_scores_codex":[0.9987642,0.00006614075,0.0001808102,0.0002355794,0.0006515294,0.0001017097],"domain_scores_gemma":[0.9990595,0.00002478009,0.00008174124,0.0004295908,0.0003652331,0.0000391451],"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":[1.474008e-7,0.00006817447,0.00001914502,0.000001937208,0.000004656375,8.693004e-7,0.0005457182,0.00001135546,0.0009742305,0.002944637,0.0006681308,0.994761],"study_design_scores_gemma":[0.0000857054,0.0000445482,0.0001925657,0.00002336431,0.000008379619,0.000001999057,0.000008680729,0.8455234,0.041769,0.1121086,0.0001518326,0.00008192012],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.003905527,0.0003325361,0.9424729,0.0005665242,0.0000600279,0.00009067236,9.41768e-7,0.000495811,0.05207499],"genre_scores_gemma":[0.4561425,0.000003675821,0.5434693,0.000279393,0.00001600716,0.000006686196,0.000001192329,0.000004298583,0.00007699674],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9946791,"threshold_uncertainty_score":0.2497723,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1053539448644674,"score_gpt":0.3424969503739186,"score_spread":0.2371430055094512,"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."}}