{"id":"W3009393055","doi":"10.1007/s10463-022-00828-4","title":"On the rate of convergence of image classifiers based on convolutional neural networks","year":2022,"lang":"en","type":"article","venue":"Annals of the Institute of Statistical Mathematics","topic":"Anomaly Detection Techniques and Applications","field":"Computer Science","cited_by":14,"is_retracted":false,"has_abstract":false,"ca_institutions":"Concordia University","funders":"","keywords":"Convolutional neural network; Pattern recognition (psychology); Curse of dimensionality; Artificial intelligence; Rate of convergence; Convergence (economics); Artificial neural network; Dimension (graph theory); Image (mathematics); Contextual image classification; Computer science; Mathematics; Algorithm; Machine learning","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":[],"consensus_categories":[],"category_scores_codex":[0.0004878993,0.00008534059,0.0001969706,0.00004299107,0.0001339505,0.000006331554,0.000816344,0.00002343194,0.00006845327],"category_scores_gemma":[0.0002544076,0.0000553104,0.0001002077,0.0003234429,0.000558953,0.00004997557,0.0001931284,0.0001537451,7.716528e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001005406,"about_ca_system_score_gemma":0.0000687349,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002052332,"about_ca_topic_score_gemma":6.585861e-7,"domain_scores_codex":[0.9989161,0.00008630401,0.0004418192,0.0001215536,0.0003286184,0.0001055611],"domain_scores_gemma":[0.9980331,0.0007913526,0.0004577276,0.0005265806,0.0001621781,0.00002905943],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001700633,0.0002000942,0.000005214757,0.00004427003,0.00001241873,4.330872e-7,0.00003446641,0.02266489,0.0007127192,0.97314,0.002868401,0.0003001069],"study_design_scores_gemma":[0.000082465,0.0002355357,0.0002788655,0.00003809509,0.000009411996,0.000001512818,0.00002123407,0.8295255,0.01262346,0.1569485,0.0001796256,0.00005577261],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01432936,0.000006011903,0.9816763,0.002750365,0.0001200213,0.0002404854,0.0001701946,0.00001432013,0.0006929567],"genre_scores_gemma":[0.9642093,0.000004399226,0.03524264,0.0004766849,0.000005394959,0.00002865481,0.000002353686,0.000004405695,0.00002620826],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9498799,"threshold_uncertainty_score":0.2255493,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04806473823247821,"score_gpt":0.2954215988966239,"score_spread":0.2473568606641457,"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."}}