{"id":"W7067390008","doi":"","title":"License Plate Detection and Character Recognition using Deep Learning and Font Evaluation","year":2024,"lang":"en","type":"dissertation","venue":"Spectrum Research Repository (Concordia University)","topic":"Indian and Buddhist Studies","field":"Arts and Humanities","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Deep learning; License; Font; Task (project management); Pattern recognition (psychology); Optical character recognition; Character recognition; Character (mathematics)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001153364,0.001832215,0.0007822724,0.003341256,0.000467714,0.001748424,0.001602056,0.001092538,0.008447376],"category_scores_gemma":[0.004073909,0.0002416331,0.001034828,0.001448549,0.0005076373,0.00167924,0.001377417,0.001114468,0.006381445],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001136464,"about_ca_system_score_gemma":0.001008655,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0252619,"about_ca_topic_score_gemma":0.03355712,"domain_scores_codex":[0.9984938,0.0001967896,0.0001401046,0.00033369,0.0005985448,0.0002369802],"domain_scores_gemma":[0.9980454,0.000377565,0.0001458648,0.0002878322,0.000938923,0.0002042617],"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":[0.002187925,0.001687911,0.03383883,0.001055399,0.0004973634,0.001163134,0.0001294708,0.07144505,0.02793101,0.001765125,0.07757627,0.7807225],"study_design_scores_gemma":[0.00009468966,0.0005140781,0.02701003,0.0001326565,0.0001424717,0.0004844923,0.0003643325,0.8927004,0.06294789,0.001069059,0.0144385,0.000101377],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.7906082,0.004941115,0.087839,0.0009301321,0.00167501,0.0008171727,0.03565124,0.02132883,0.05620936],"genre_scores_gemma":[0.8447586,0.0009456102,0.05333558,0.00044122,0.0001852911,0.0002210242,0.07763587,0.00044782,0.02202888],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.0252619,"threshold_uncertainty_score":0.05022973,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05808078718809098,"score_gpt":0.2883455177811282,"score_spread":0.2302647305930372,"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."}}