{"id":"W4416365769","doi":"10.1117/12.3092610","title":"An improved YOLOv11 framework for robust helmet detection with focus on small-scale target detection","year":2025,"lang":"","type":"article","venue":"","topic":"Advanced Neural Network Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Focus (optics); Feature (linguistics); Object detection; Pooling; Residual; Feature extraction; Component (thermodynamics)","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","sts"],"consensus_categories":[],"category_scores_codex":[0.0003627905,0.0006420782,0.0005029337,0.0003843717,0.001303461,0.0004654842,0.001188753,0.0005104008,0.00002556794],"category_scores_gemma":[0.00009345697,0.0005891788,0.0001940146,0.002733816,0.0001776342,0.0007935963,0.0001967975,0.000837738,0.00002693657],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003384347,"about_ca_system_score_gemma":0.0001532646,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008318842,"about_ca_topic_score_gemma":0.001889434,"domain_scores_codex":[0.9958717,0.000168117,0.0006868393,0.00200261,0.0002863703,0.0009844236],"domain_scores_gemma":[0.9961667,0.000684367,0.0003998179,0.00200666,0.0004364384,0.0003060339],"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":[0.0009601946,0.0006061116,0.0000657631,0.00006745094,0.00009068085,0.000001506858,0.000156659,0.08416457,0.02923921,0.02302084,0.00003627487,0.8615907],"study_design_scores_gemma":[0.0007244754,0.002732004,0.0003802426,0.00008568106,0.00006370657,0.000007863856,0.00006210898,0.6598586,0.2734555,0.06130948,0.0008192854,0.0005010375],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.006212499,0.000107064,0.9862676,0.00161649,0.001287802,0.003191962,0.000016804,0.000699422,0.0006003887],"genre_scores_gemma":[0.5299687,0.0000235284,0.4675838,0.0006484474,0.0002849986,0.0008922523,0.000004613889,0.00004202946,0.0005515977],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8610897,"threshold_uncertainty_score":0.9999967,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01616501951215468,"score_gpt":0.2624042991954268,"score_spread":0.2462392796832722,"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."}}