{"id":"W2128624929","doi":"10.1109/icassp.1998.678128","title":"Grid filters for local nonlinear image restoration","year":2002,"lang":"en","type":"article","venue":"","topic":"Image and Signal Denoising Methods","field":"Computer Science","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Pixel; Grid; Filter (signal processing); Algorithm; Computer science; Noise (video); Nonlinear system; Nonlinear filter; Image restoration; Image (mathematics); Computational complexity theory; Mathematics; Artificial intelligence; Computer vision; Image processing; Filter design; Geometry","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":[0.0002502006,0.0003671906,0.0004951801,0.0003565197,0.0003047518,0.0004289062,0.0005303197,0.0005041307,0.003775448],"category_scores_gemma":[0.000781978,0.0001950183,0.0003590795,0.0005477105,0.0005092021,0.0007549292,0.0005591356,0.0008122071,0.001357087],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003568992,"about_ca_system_score_gemma":0.0003909132,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001410436,"about_ca_topic_score_gemma":0.002366177,"domain_scores_codex":[0.9998302,0.00003795947,0.000006872664,0.00002754044,0.0000822037,0.0000150362],"domain_scores_gemma":[0.9997653,0.00009741165,0.00002239788,0.00004857851,0.00005262537,0.00001356875],"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":[0.0002150373,0.00006964928,0.000568188,0.0003258034,0.00006770833,0.0001585214,0.0001227399,0.1579148,0.06247376,0.1451473,0.01229681,0.6206397],"study_design_scores_gemma":[0.00002822291,0.0001019863,0.0002713093,0.0000229915,0.00002638574,0.0002304147,0.00002965763,0.8848531,0.02910605,0.05537906,0.02992531,0.00002549937],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.002628928,0.0004430221,0.9950722,0.00006306,0.00004143064,0.00001181404,0.00002070038,0.0004620181,0.001256698],"genre_scores_gemma":[0.09124076,0.001226211,0.8994039,0.0001180025,0.00009117847,0.0001014871,0.000144623,0.0002404036,0.007433454],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003775448,"threshold_uncertainty_score":0.01263011,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03721884266556397,"score_gpt":0.2863393494048639,"score_spread":0.2491205067393,"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."}}