{"id":"W2164960992","doi":"10.1109/ultsym.2015.0197","title":"Simulation studies of filtered spatial compounding (FSC) and filtered frequency compounding (FFC) in synthetic transmit aperture (STA) imaging","year":2015,"lang":"en","type":"article","venue":"","topic":"Ultrasonics and Acoustic Wave Propagation","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"Natural Sciences and Engineering Research Council of Canada; Centre National de la Recherche Scientifique","keywords":"Speckle pattern; Compounding; Optics; Speckle noise; Signal-to-noise ratio (imaging); Aperture (computer memory); Frequency domain; Contrast-to-noise ratio; Filter (signal processing); Materials science; Physics; Computer science; Image quality; Acoustics; Artificial intelligence; Computer vision; Image (mathematics)","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0005114399,0.0004012828,0.0003334195,0.0005263439,0.0003069253,0.0004934185,0.00043921,0.001042612,0.001168162],"category_scores_gemma":[0.001767022,0.0002080675,0.0005391912,0.0005154968,0.0003819704,0.0004524748,0.000257721,0.0003108822,0.0001132456],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006776436,"about_ca_system_score_gemma":0.0005121991,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009623821,"about_ca_topic_score_gemma":0.005646485,"domain_scores_codex":[0.9998469,0.00004323546,0.000008209684,0.00001760479,0.00005615483,0.00002786783],"domain_scores_gemma":[0.9986963,0.0009780799,0.0001088686,0.00003535656,0.0001439514,0.00003758969],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00007028152,0.00003517078,0.001947661,0.00007056319,0.00001472785,0.000140834,0.00008283951,0.9847632,0.003975654,0.002111102,0.0002394605,0.006548469],"study_design_scores_gemma":[0.000004242382,0.00001788167,0.0002140865,0.000003513733,0.000003682901,0.00002343546,0.00000795609,0.9985768,0.0008421944,0.0001597192,0.0001414667,0.000005038991],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6955729,0.001573035,0.2839844,0.0005294405,0.00007246019,0.0001153906,0.000272274,0.0004561505,0.01742395],"genre_scores_gemma":[0.9653975,0.0004131364,0.03218623,0.00003861127,0.000009531618,0.00005692743,0.00009529524,0.00003708372,0.001765749],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009623821,"threshold_uncertainty_score":0.01913559,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04360250691003785,"score_gpt":0.2728302995614914,"score_spread":0.2292277926514535,"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."}}