{"id":"W2943076207","doi":"10.1109/iscas.2019.8702332","title":"Bit-Slicing FPGA Accelerator for Quantized Neural Networks","year":2019,"lang":"en","type":"article","venue":"","topic":"Advanced Neural Network Applications","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal; IBM (Canada); Université de Montréal","funders":"","keywords":"Stratix; Computer science; Field-programmable gate array; Artificial neural network; Key (lock); Hardware acceleration; Computer hardware; Computer architecture; Artificial intelligence","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":[0.0001820542,0.0003315592,0.0002127853,0.0003424253,0.0001827621,0.0003694728,0.0006157661,0.0001841956,0.01149045],"category_scores_gemma":[0.0004123733,0.000124554,0.0001265804,0.0003338639,0.0001500167,0.0004826479,0.0002428299,0.0003437116,0.001196534],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000543154,"about_ca_system_score_gemma":0.0006780897,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001681672,"about_ca_topic_score_gemma":0.002375357,"domain_scores_codex":[0.9998511,0.00002396443,0.00001162647,0.00002319615,0.00006359859,0.00002632562],"domain_scores_gemma":[0.9997965,0.0000566666,0.000023215,0.00003373452,0.00007368555,0.00001628581],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.002252222,0.000275134,0.004333511,0.0006890821,0.0001411098,0.0009228725,0.0003583493,0.06415823,0.2922453,0.04946596,0.05006135,0.5350968],"study_design_scores_gemma":[0.0003324616,0.001209521,0.002426754,0.00008897384,0.00008495523,0.0005537107,0.0001109169,0.704676,0.2270016,0.009946307,0.05349945,0.00006931913],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3511184,0.001376865,0.5941405,0.0006036225,0.000433244,0.0001917166,0.0008781126,0.01635605,0.03490148],"genre_scores_gemma":[0.8207867,0.0002353748,0.1672779,0.000200158,0.00003956411,0.00009436416,0.000650654,0.000176337,0.01053905],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01149045,"threshold_uncertainty_score":0.03843933,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02661303888792212,"score_gpt":0.2842261038776424,"score_spread":0.2576130649897203,"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."}}