{"id":"W565356442","doi":"10.1016/j.patrec.2015.06.008","title":"Document image binarization using a discriminative structural classifier","year":2015,"lang":"en","type":"article","venue":"Pattern Recognition Letters","topic":"Handwritten Text Recognition Techniques","field":"Computer Science","cited_by":30,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"CRFS; Discriminative model; Artificial intelligence; Computer science; Pattern recognition (psychology); Conditional random field; Pixel; Classifier (UML); Graphical model; Image (mathematics)","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":[0.0003764144,0.0005978423,0.0009730972,0.001579748,0.0004869052,0.0008835571,0.0006622871,0.0005393956,0.004280785],"category_scores_gemma":[0.0008387004,0.0003189532,0.0007039909,0.00147118,0.0003113784,0.0008691087,0.0006819174,0.0009061805,0.004082785],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004051657,"about_ca_system_score_gemma":0.0009276823,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002264818,"about_ca_topic_score_gemma":0.005525603,"domain_scores_codex":[0.9995968,0.00003801073,0.00002808692,0.0001175649,0.0001583267,0.00006116603],"domain_scores_gemma":[0.9993642,0.00009581011,0.00004422314,0.000144443,0.0002992563,0.00005215707],"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":[0.0003185564,0.0001656839,0.00081086,0.00008603473,0.00003917196,0.00004915336,0.00002490311,0.004380371,0.2130018,0.001798453,0.003096228,0.7762288],"study_design_scores_gemma":[0.00004442568,0.0003973269,0.008293765,0.00002735194,0.0001762689,0.0006787156,0.00007112024,0.7078706,0.2675513,0.002225431,0.01262022,0.00004348662],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0338241,0.0004328734,0.9603901,0.0001449826,0.000146986,0.00008924371,0.0002143503,0.002835488,0.00192183],"genre_scores_gemma":[0.2973543,0.0007882121,0.6836997,0.0002399185,0.0002032401,0.0001301384,0.001808716,0.0004219001,0.01535388],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.004280785,"threshold_uncertainty_score":0.01432061,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05941645178811838,"score_gpt":0.2969398672257366,"score_spread":0.2375234154376182,"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."}}