{"id":"W2007163663","doi":"10.1109/icdar.2013.65","title":"Feature Design for Offline Arabic Handwriting Recognition: Handcrafted vs Automated?","year":2013,"lang":"en","type":"article","venue":"","topic":"Handwritten Text Recognition Techniques","field":"Computer Science","cited_by":39,"is_retracted":false,"has_abstract":true,"ca_institutions":"École de Technologie Supérieure","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Artificial intelligence; Heuristics; Benchmark (surveying); Feature (linguistics); Task (project management); Handwriting recognition; Connectionism; Artificial neural network; Intelligent character recognition; Pattern recognition (psychology); Handwriting; Probabilistic logic; Feature extraction; Machine learning; Speech recognition; Natural language processing; Image (mathematics)","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006391616,0.0009081275,0.0007427853,0.0007113727,0.0002066809,0.0007834056,0.0007298698,0.0007771849,0.003846795],"category_scores_gemma":[0.002653564,0.0002217261,0.0003598869,0.0006653049,0.0002483056,0.001579681,0.0004462305,0.0007420018,0.001648766],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000349547,"about_ca_system_score_gemma":0.0004574519,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001498686,"about_ca_topic_score_gemma":0.002324463,"domain_scores_codex":[0.9995648,0.00008307682,0.00004268446,0.0001448807,0.0001119974,0.00005255168],"domain_scores_gemma":[0.9990723,0.0003884463,0.0001159502,0.0001856835,0.0001967201,0.00004073905],"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":[0.0004480848,0.0001658644,0.001864029,0.0002114198,0.00006289251,0.00009918623,0.00003324912,0.02832296,0.03658037,0.000572948,0.003600423,0.9280387],"study_design_scores_gemma":[0.00009830956,0.0007059237,0.006437634,0.00006692586,0.0000727736,0.0004335454,0.00008279892,0.8862188,0.09720792,0.002801092,0.005826254,0.00004797388],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2463506,0.003380865,0.7321051,0.0003662835,0.0002541263,0.0002667813,0.001072603,0.01085449,0.005349204],"genre_scores_gemma":[0.7492746,0.0006568758,0.2444607,0.0001386971,0.00007606711,0.0001500087,0.001955515,0.0002438764,0.003043604],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003846795,"threshold_uncertainty_score":0.01286882,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0314695678777866,"score_gpt":0.26387193234847,"score_spread":0.2324023644706834,"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."}}