{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","open_science"],"consensus_categories":[],"category_scores_codex":[0.002184958,0.0004139354,0.0004785925,0.0007383843,0.0006436945,0.0006165558,0.008187549,0.0001245197,0.0003898194],"category_scores_gemma":[0.0004495487,0.00046137,0.00009369228,0.0008790128,0.0001407304,0.001849486,0.006346155,0.001097085,0.00003311],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000224227,"about_ca_system_score_gemma":0.0003142018,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003411322,"about_ca_topic_score_gemma":0.0001072685,"domain_scores_codex":[0.9945787,0.0004392822,0.000944462,0.001770491,0.001756982,0.0005101204],"domain_scores_gemma":[0.9957981,0.0002104765,0.000779931,0.00259334,0.0004585033,0.000159685],"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":[0.00008854218,0.0005659429,0.00011499,0.00003905486,0.0001829366,0.0000317223,0.0005101248,0.0005151468,0.03885971,0.001000616,0.002104329,0.9559869],"study_design_scores_gemma":[0.001092605,0.00020652,0.00006872723,0.0001708773,0.0000493118,0.0001825455,0.0007388224,0.9826981,0.004698668,0.0009649312,0.008440451,0.0006884299],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01797709,0.00007724106,0.9692883,0.0004839903,0.00259555,0.0004750934,0.00595841,0.0003254818,0.002818879],"genre_scores_gemma":[0.7828411,0.0002200504,0.1856927,0.0006767326,0.001273522,0.0001982605,0.02870318,0.00007180277,0.0003225667],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.982183,"threshold_uncertainty_score":0.9997838,"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."}}