{"id":"W4411035050","doi":"10.18280/jesa.580404","title":"FPGA based Fuzzy Edge Detection System for COVID-19 X-Ray Images","year":2025,"lang":"en","type":"article","venue":"Journal Européen des Systèmes Automatisés","topic":"Brain Tumor Detection and Classification","field":"Neuroscience","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Field-programmable gate array; Coronavirus disease 2019 (COVID-19); Enhanced Data Rates for GSM Evolution; Computer science; Fuzzy logic; Edge detection; Computer vision; Artificial intelligence; Image (mathematics); Embedded system; Image processing; Medicine; Internal medicine","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":["metaepi_narrow","sts"],"consensus_categories":[],"category_scores_codex":[0.001136157,0.0002883758,0.0003552549,0.0006076174,0.001533411,0.0006143993,0.0004631509,0.0001270579,0.00005170642],"category_scores_gemma":[0.003724515,0.000258422,0.0002774773,0.0009353572,0.0001916686,0.000396728,0.00004532985,0.0003601181,0.00009896773],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001133426,"about_ca_system_score_gemma":0.0004634829,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001369095,"about_ca_topic_score_gemma":0.00001090589,"domain_scores_codex":[0.9969446,0.0008442461,0.0008004312,0.0005217432,0.0004339201,0.0004550746],"domain_scores_gemma":[0.9975477,0.0009021446,0.0005949667,0.0004039809,0.0002198455,0.0003313197],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0002133511,0.0001346703,0.0001045868,0.001507369,0.00003624194,0.00007673635,0.0001817001,0.001609386,0.7507846,0.003193367,0.007145145,0.2350128],"study_design_scores_gemma":[0.004414855,0.0005376128,0.04452888,0.0007513133,0.0002074853,0.001901982,0.0008931622,0.1015856,0.7804913,0.005106471,0.05877849,0.0008027822],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04500795,0.0003107149,0.9342684,0.002573577,0.004256193,0.001323095,0.0000702226,0.001651063,0.01053875],"genre_scores_gemma":[0.99308,0.00002464824,0.001858543,0.001576994,0.000250259,0.000139496,0.00000213543,0.00004913533,0.003018771],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9480721,"threshold_uncertainty_score":0.9999868,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03696836855131192,"score_gpt":0.2963879420926847,"score_spread":0.2594195735413728,"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."}}