{"id":"W4285035345","doi":"10.3390/math10142421","title":"Application of Smooth Fuzzy Model in Image Denoising and Edge Detection","year":2022,"lang":"en","type":"article","venue":"Mathematics","topic":"Medical Image Segmentation Techniques","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Agencia Estatal de Investigación; Universidad Carlos III de Madrid; Ministerio de Ciencia e Innovación; Comunidad de Madrid","keywords":"Fuzzy logic; Bounded function; Mathematics; Standard deviation; Gaussian; Impulse noise; Gaussian noise; Digital image; Impulse (physics); Algorithm; Artificial intelligence; Pattern recognition (psychology); Image (mathematics); Computer science; Image processing; Mathematical analysis; Statistics; Chemistry; Physics; Pixel","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":[0.001039968,0.0006211365,0.0007607496,0.0009131547,0.0004073962,0.0007615188,0.0005639416,0.0009207504,0.0006407392],"category_scores_gemma":[0.001826486,0.0002890892,0.001054928,0.0005877205,0.0007403553,0.001114169,0.0005748111,0.0006736041,0.0001803857],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000451738,"about_ca_system_score_gemma":0.0004975926,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002037844,"about_ca_topic_score_gemma":0.001596086,"domain_scores_codex":[0.9994635,0.0001354487,0.00002160283,0.0001189682,0.0002256143,0.0000348612],"domain_scores_gemma":[0.999619,0.0001799371,0.00003827097,0.00004723198,0.00009923875,0.0000162486],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0003110594,0.00007470204,0.00171171,0.0004178527,0.000201954,0.0003760991,0.0003344395,0.6312129,0.07820196,0.09210601,0.00073962,0.1943117],"study_design_scores_gemma":[0.000004925606,0.00009737547,0.0002731385,0.00001056109,0.00002785518,0.0001246354,0.00002620121,0.9696904,0.009945563,0.01846274,0.001316927,0.00001976275],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02659393,0.0008061134,0.9709759,0.00008013396,0.00002806605,0.00001749755,0.00001388692,0.0001031401,0.001381232],"genre_scores_gemma":[0.7543664,0.001468113,0.2409955,0.0000752633,0.00006307524,0.00003465876,0.00006983197,0.00005129301,0.002875854],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002037844,"threshold_uncertainty_score":0.005499959,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01436098867917018,"score_gpt":0.2702706777795674,"score_spread":0.2559096891003972,"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."}}