{"id":"W3045424063","doi":"10.22581/muet1982.2003.13","title":"A Multi-blocked Image Classifier for Deep Learning","year":2020,"lang":"en","type":"article","venue":"Mehran University Research Journal of Engineering and Technology","topic":"Advanced Neural Network Applications","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Sungkyunkwan University","keywords":"MNIST database; Overfitting; Computer science; Convolutional neural network; Dropout (neural networks); Artificial intelligence; Deep learning; Machine learning; Classifier (UML); Artificial neural network; Contextual image classification; Data mining; Deep neural networks; Pattern recognition (psychology); Image (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":[0.0008863017,0.0009755121,0.000968302,0.001179568,0.0004787002,0.00089353,0.003008184,0.001607267,0.004157367],"category_scores_gemma":[0.001605244,0.0004692909,0.001192245,0.0009676786,0.0003849233,0.00194828,0.001443654,0.002070786,0.002326158],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001266618,"about_ca_system_score_gemma":0.001609058,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007181831,"about_ca_topic_score_gemma":0.009258211,"domain_scores_codex":[0.99934,0.0001050544,0.00003401947,0.0001514397,0.0002523698,0.0001171257],"domain_scores_gemma":[0.9994442,0.0000967806,0.00005193619,0.000123938,0.0002308738,0.00005227877],"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":[0.000564622,0.0003937427,0.003253905,0.0001549854,0.000276248,0.0002142999,0.000065596,0.1779683,0.02609677,0.01630628,0.02576029,0.7489449],"study_design_scores_gemma":[0.00001215593,0.00004683438,0.0002105406,0.000008509406,0.00001448482,0.00004596734,0.000005199156,0.9899788,0.004478601,0.002376529,0.00281419,0.000008281617],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01685696,0.0009982821,0.9763994,0.000263786,0.0001815843,0.0001262693,0.0004803625,0.002719903,0.001973599],"genre_scores_gemma":[0.3929263,0.001071921,0.5793148,0.0007522255,0.0002222815,0.0005714205,0.005727495,0.00051702,0.01889655],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007181831,"threshold_uncertainty_score":0.01428002,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03723065329813031,"score_gpt":0.2837392438525288,"score_spread":0.2465085905543985,"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."}}