{"id":"W4250057196","doi":"10.32920/ryerson.14663658","title":"Convolutional neural network for image classification based on transfer learning technique","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Neural Networks and Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Computer science; Convolutional neural network; Artificial intelligence; Transfer of learning; Artificial neural network; Deep learning; Contextual image classification; Machine learning; Interface (matter); Network architecture; MATLAB; Time delay neural network; Pattern recognition (psychology); Image (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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006017181,0.0007091421,0.0005820647,0.0008514066,0.0002981983,0.0007925991,0.001081126,0.0009431666,0.004551039],"category_scores_gemma":[0.001618581,0.0002930732,0.0007992058,0.001357723,0.0006623871,0.001641732,0.0009517895,0.001934583,0.002767626],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009978299,"about_ca_system_score_gemma":0.0006973356,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003008518,"about_ca_topic_score_gemma":0.002517933,"domain_scores_codex":[0.9996065,0.00005621408,0.00002397285,0.0000934717,0.0001761633,0.00004371486],"domain_scores_gemma":[0.9996895,0.00009875339,0.00003125027,0.00007086371,0.00009378824,0.00001597541],"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":[0.0001269127,0.0001101683,0.0007319872,0.0004085976,0.0001384304,0.00021834,0.0001037696,0.265771,0.04147767,0.1043428,0.01369048,0.5728799],"study_design_scores_gemma":[0.000005008229,0.00002612812,0.0003378413,0.00002389885,0.00001471673,0.00009347349,0.000007013481,0.9567667,0.01039739,0.02311921,0.009194064,0.00001449793],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.004064761,0.001024323,0.9889228,0.0001978357,0.0001241441,0.00004980441,0.0001026478,0.001419807,0.004093816],"genre_scores_gemma":[0.2729371,0.00283374,0.7039545,0.0002727591,0.0002505846,0.0002940741,0.0007992916,0.0005317607,0.01812617],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004551039,"threshold_uncertainty_score":0.01522481,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03467951178793252,"score_gpt":0.2771902292258709,"score_spread":0.2425107174379384,"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."}}