{"id":"W1593272421","doi":"10.1109/mwscas.2002.1187129","title":"Fuzzy filters for image filtering","year":2003,"lang":"en","type":"article","venue":"","topic":"Image and Signal Denoising Methods","field":"Computer Science","cited_by":44,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Windsor","funders":"","keywords":"Pixel; Impulse noise; Fuzzy logic; Artificial intelligence; Computer vision; Computer science; Median filter; Impulse (physics); Window (computing); Filtering theory; Image (mathematics); Mathematics; Pattern recognition (psychology); Image processing","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":[0.0008771172,0.0005681799,0.0008053631,0.0008464475,0.0004468021,0.001046393,0.0006008839,0.001734716,0.003108555],"category_scores_gemma":[0.001986839,0.0002590199,0.0007797445,0.001059817,0.000994912,0.001233269,0.0004746796,0.001643684,0.001273658],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007639935,"about_ca_system_score_gemma":0.00048358,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002170965,"about_ca_topic_score_gemma":0.00181405,"domain_scores_codex":[0.9993889,0.0001080333,0.00003896784,0.0001205104,0.0003106184,0.0000329145],"domain_scores_gemma":[0.9995863,0.0001974142,0.00003394977,0.00004739024,0.0001216556,0.00001324387],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001089153,0.00004371766,0.0003148778,0.000743587,0.0001339828,0.0002432337,0.0002043579,0.05945709,0.02358946,0.5200318,0.007576977,0.3875521],"study_design_scores_gemma":[0.00005047254,0.0001823441,0.0006104681,0.0002550535,0.000104237,0.0007465006,0.00008727505,0.4837959,0.01824951,0.3542802,0.1415322,0.0001057269],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001591589,0.006596549,0.9857358,0.0003368788,0.0002727958,0.00002050217,0.00003120322,0.0001517977,0.005262719],"genre_scores_gemma":[0.1341868,0.01818193,0.8263327,0.0007651475,0.0009300205,0.0001703388,0.0002033822,0.00008336797,0.01914631],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.003108555,"threshold_uncertainty_score":0.01039916,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02933097085062463,"score_gpt":0.2924327604976075,"score_spread":0.2631017896469828,"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."}}