{"id":"W2991796308","doi":"10.18280/ria.330407","title":"Compact Hardware of Running Gaussian Average Algorithm for Moving Object Detection Realized on FPGA and ASIC","year":2019,"lang":"en","type":"article","venue":"Revue d intelligence artificielle","topic":"Video Surveillance and Tracking Methods","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Field-programmable gate array; Application-specific integrated circuit; Computer science; Gaussian; Computer hardware; FPGA prototype; Embedded system; Object (grammar); Artificial intelligence; Physics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001008629,0.0001773108,0.0003435079,0.0001710792,0.0001506418,0.0001045302,0.0003691865,0.00008135254,0.00002401158],"category_scores_gemma":[0.000114607,0.0001695092,0.0001252859,0.0003867839,0.00004213888,0.0002602705,0.00006636353,0.0001635718,0.00003887311],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004032652,"about_ca_system_score_gemma":0.00003132068,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006808989,"about_ca_topic_score_gemma":0.000008878628,"domain_scores_codex":[0.9984933,0.0001046321,0.000401343,0.0005082656,0.0001758429,0.0003166257],"domain_scores_gemma":[0.9985073,0.0005166484,0.0002072856,0.0005895499,0.0001038716,0.00007541139],"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":[0.00003356704,0.00006462986,0.0007948445,0.0001331766,0.00002738198,0.000005349686,0.001236865,0.0177588,0.01332432,0.002237074,0.00002672453,0.9643573],"study_design_scores_gemma":[0.0001145667,0.0003423393,0.001038951,0.0001846353,0.000005278157,0.00001712286,0.0001421296,0.7136467,0.2815874,0.001763347,0.0009699748,0.0001875778],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04535558,0.0001444237,0.9517943,0.0001053868,0.0005065729,0.0004070748,0.000006639537,0.00009487045,0.001585178],"genre_scores_gemma":[0.9602595,0.00004286322,0.03912047,0.00006314189,0.00005994977,0.00001144398,0.000003439528,0.00001776656,0.0004214353],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9641697,"threshold_uncertainty_score":0.6912385,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03851916740797801,"score_gpt":0.3026671273518354,"score_spread":0.2641479599438574,"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."}}