{"id":"W2155440966","doi":"10.1109/icpr.1992.201940","title":"Binary character/graphics image extraction: a new technique and six evaluation aspects","year":2003,"lang":"en","type":"article","venue":"","topic":"Handwritten Text Recognition Techniques","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Grayscale; Character (mathematics); Computer science; Graphics; Artificial intelligence; Font; Binary number; Image (mathematics); Computer graphics; Quality (philosophy); Computer vision; Information retrieval; Pattern recognition (psychology); Computer graphics (images); Mathematics; Arithmetic","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":[0.006052132,0.00177562,0.001904641,0.00621739,0.0007507724,0.00389783,0.001532519,0.002117195,0.003166993],"category_scores_gemma":[0.01607895,0.0007419873,0.001499856,0.004903523,0.001400534,0.005548023,0.001081304,0.00115043,0.003049554],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009102945,"about_ca_system_score_gemma":0.0008017306,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008415526,"about_ca_topic_score_gemma":0.001446985,"domain_scores_codex":[0.9896549,0.00176382,0.001845347,0.0008286823,0.005715752,0.0001915545],"domain_scores_gemma":[0.9749067,0.008522474,0.001818233,0.002461663,0.0118612,0.0004297051],"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":[0.000559905,0.0004014514,0.002921965,0.001405572,0.0001998304,0.0001848265,0.0003092608,0.001491735,0.0807998,0.001100238,0.00349085,0.9071345],"study_design_scores_gemma":[0.0002549299,0.007129657,0.03376259,0.0006768792,0.001811817,0.01045941,0.001239832,0.09267627,0.7724504,0.004012666,0.07478464,0.0007409235],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04711988,0.01008201,0.9271781,0.0004971336,0.0005685981,0.0009297116,0.0003007465,0.003725037,0.009598713],"genre_scores_gemma":[0.142159,0.01012032,0.8322945,0.0002893698,0.0006979344,0.0007867041,0.00119067,0.0008102174,0.01165121],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00621739,"threshold_uncertainty_score":0.03200716,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02599451987807253,"score_gpt":0.2993660126031,"score_spread":0.2733714927250275,"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."}}