{"id":"W2122364308","doi":"10.1109/ccece.2005.1557200","title":"Analysis of the coefficients of generalized bilinear transformation in the design of 2-D band-pass and band-stop filters and an application in image processing","year":2006,"lang":"en","type":"article","venue":"","topic":"Digital Filter Design and Implementation","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Bilinear transform; m-derived filter; Low-pass filter; Prototype filter; Bilinear interpolation; Network synthesis filters; Passband; High-pass filter; Butterworth filter; Filter design; Computer science; Band-pass filter; Filter (signal processing); Transition band; Digital filter; Composite image filter; Algorithm; Mathematics; Electronic engineering; Engineering; Computer vision; Image (mathematics)","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":[0.0004164846,0.0003852689,0.00015749,0.0002937689,0.0001730347,0.0004418993,0.000175352,0.0002852883,0.001336581],"category_scores_gemma":[0.001823458,0.000220356,0.000212353,0.0004580873,0.0003187812,0.0006317761,0.0002273321,0.0004362577,0.0003426939],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001750405,"about_ca_system_score_gemma":0.0002216612,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005204426,"about_ca_topic_score_gemma":0.0007459966,"domain_scores_codex":[0.9997516,0.00009676256,0.000009973255,0.00002167184,0.00009637125,0.00002353524],"domain_scores_gemma":[0.9995232,0.0002486075,0.00006009696,0.00003982149,0.0001086989,0.00001972006],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0006197059,0.000119623,0.004260824,0.0004455092,0.0000469334,0.0006708934,0.0009708838,0.2642933,0.2874292,0.1858683,0.001443869,0.253831],"study_design_scores_gemma":[0.00001962052,0.0002660586,0.001438045,0.00003566573,0.0000239426,0.0006039072,0.0001961091,0.8963783,0.0641736,0.02692107,0.009909808,0.0000338773],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.07514659,0.000337983,0.9208221,0.0000708767,0.00003112236,0.00003019038,0.0000208917,0.00006718989,0.003473123],"genre_scores_gemma":[0.7963053,0.0008188867,0.1973889,0.00003108915,0.00002457554,0.0000604423,0.00005951992,0.00004853596,0.005262712],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.001336581,"threshold_uncertainty_score":0.004471302,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02002982037270789,"score_gpt":0.2782630230443091,"score_spread":0.2582332026716012,"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."}}