{"id":"W2095849288","doi":"10.1109/ispa.2003.1296386","title":"Adaptive weighted median filter using local entropy for ultrasonic image de-noising","year":2004,"lang":"en","type":"article","venue":"","topic":"Image and Signal Denoising Methods","field":"Computer Science","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Adaptive filter; Kernel adaptive filter; Entropy (arrow of time); Filter (signal processing); Speckle pattern; Artificial intelligence; Bilateral filter; Filter design; Median filter; Mathematics; Computer vision; Computer science; Algorithm; Pattern recognition (psychology); Image processing; Image (mathematics); Physics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00056199,0.0001859654,0.0002094386,0.0001236492,0.0002194962,0.0002528436,0.0005483799,0.00008730904,0.00003472474],"category_scores_gemma":[0.00007101594,0.000160439,0.0001374187,0.0003070514,0.0001057283,0.0007286893,0.00008963911,0.0001460486,0.00002730131],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002580222,"about_ca_system_score_gemma":0.0002814579,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000183106,"about_ca_topic_score_gemma":0.00001252494,"domain_scores_codex":[0.9984306,0.0001129496,0.0002379509,0.0004130666,0.0002316153,0.0005738377],"domain_scores_gemma":[0.9990136,0.0002612215,0.00006969891,0.0003488048,0.0001457422,0.000160931],"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":[0.0001930021,0.0002666862,0.00003721099,0.00005327457,0.0001287215,0.0003268146,0.003865344,0.003692714,0.5649276,0.1400013,0.0008855955,0.2856217],"study_design_scores_gemma":[0.0018663,0.0001812889,0.00005997101,0.00006093448,0.00002425566,0.0001242407,0.00009690363,0.4379815,0.4858739,0.07293675,0.0004501553,0.0003438335],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.006759595,0.00007206101,0.99108,0.0006747502,0.0002796022,0.0002165287,0.00000275552,0.0001594125,0.000755308],"genre_scores_gemma":[0.2117369,0.000002990501,0.7872152,0.0007529597,0.0001362646,0.000006570046,0.000001779372,0.00001583287,0.0001315688],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.4342887,"threshold_uncertainty_score":0.6542512,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02827323041579508,"score_gpt":0.2901835148860206,"score_spread":0.2619102844702255,"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."}}