{"id":"W4318147587","doi":"10.1109/bigdata55660.2022.10021025","title":"Handwritten Word Recognition using Deep Learning Approach: A Novel Way of Generating Handwritten Words","year":2022,"lang":"en","type":"article","venue":"2022 IEEE International Conference on Big Data (Big Data)","topic":"Handwritten Text Recognition Techniques","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"","keywords":"Computer science; Word (group theory); Artificial intelligence; Word error rate; Bengali; Natural language processing; Process (computing); Speech recognition; Recall rate; Deep learning; Precision and recall; Language model; Pattern recognition (psychology); 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":[0.0003108816,0.0006081464,0.0003566104,0.0004232879,0.0001867307,0.0005349625,0.000819704,0.0005243961,0.001722932],"category_scores_gemma":[0.0007860306,0.0002343303,0.0004961052,0.0005109179,0.0003065483,0.001012566,0.0005326018,0.0008558689,0.001048249],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004120735,"about_ca_system_score_gemma":0.0006035463,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002488135,"about_ca_topic_score_gemma":0.003555537,"domain_scores_codex":[0.9996643,0.00004229293,0.00002597068,0.0001169568,0.0001117292,0.00003870727],"domain_scores_gemma":[0.9996165,0.00008458299,0.00003634679,0.00009141416,0.0001469334,0.00002414616],"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":[0.0001887415,0.0001792211,0.001492523,0.000194295,0.00006797798,0.0003602381,0.0001317388,0.07599393,0.1189753,0.003144873,0.00528243,0.7939887],"study_design_scores_gemma":[0.00002760754,0.0002131945,0.001178922,0.00002342152,0.00003424296,0.000419721,0.00004093221,0.8588541,0.1279823,0.003350697,0.007843582,0.00003122439],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07856534,0.0005364357,0.9082318,0.0002518286,0.0001903224,0.0001460274,0.0003950692,0.006392518,0.00529057],"genre_scores_gemma":[0.5356234,0.0004183974,0.4485623,0.0003514343,0.00004950159,0.0001420805,0.00171249,0.0003115068,0.012829],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002488135,"threshold_uncertainty_score":0.005763769,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3210273366955822,"score_gpt":0.3386155405561522,"score_spread":0.01758820386056997,"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."}}