{"id":"W2931400272","doi":"10.18122/td.1782.boisestate","title":"Deep Convolutional Spiking Neural Networks for Image Classification","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Advanced Memory and Neural Computing","field":"Engineering","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Ministry of Education, India; International Institute of Information Technology, Hyderabad; Canadian Institute for Advanced Research","keywords":"MNIST database; Artificial intelligence; Spiking neural network; Computer science; Stochastic gradient descent; Artificial neural network; Backpropagation; Forgetting; Pattern recognition (psychology); Convolutional neural network; Feature (linguistics); Gradient descent; Deep learning; Machine learning","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"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":[0.0004352227,0.0007732353,0.0005664869,0.0007071468,0.0002529677,0.0008522918,0.001129808,0.0009754628,0.008339938],"category_scores_gemma":[0.001581303,0.0004016598,0.0007432512,0.001593493,0.0003249181,0.001009399,0.0006696095,0.001545917,0.00286008],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001008075,"about_ca_system_score_gemma":0.0008137038,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006238899,"about_ca_topic_score_gemma":0.008601317,"domain_scores_codex":[0.9997866,0.0000226519,0.00001590814,0.0000577721,0.00008810471,0.00002907528],"domain_scores_gemma":[0.9996536,0.0001192741,0.00004429678,0.00006935532,0.00009688714,0.00001654385],"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":[0.0001451515,0.0000932793,0.00103283,0.0004119205,0.0001338258,0.0001283957,0.00005751321,0.2801704,0.02262716,0.02403327,0.02645503,0.6447112],"study_design_scores_gemma":[0.000006954442,0.00001740247,0.0003961904,0.00002855373,0.00001180135,0.00003505095,0.000008290294,0.9688702,0.005627163,0.01553117,0.009453879,0.00001339097],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01345687,0.005941383,0.9610656,0.0009494122,0.0003368267,0.00009330694,0.001748857,0.008152814,0.008254853],"genre_scores_gemma":[0.4210083,0.006899239,0.541227,0.0005979725,0.0002614644,0.0003384369,0.0053775,0.0006846786,0.02360545],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008339938,"threshold_uncertainty_score":0.02789986,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03491398023910249,"score_gpt":0.2699561131042656,"score_spread":0.2350421328651631,"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."}}