{"id":"W2004957001","doi":"10.1109/icip.2000.899408","title":"A new series of biorthogonal wavelet filters for image compression","year":2000,"lang":"en","type":"article","venue":"","topic":"Image and Signal Denoising Methods","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Biorthogonal system; Biorthogonal wavelet; Mathematics; Wavelet; Filter (signal processing); Filter design; Filter bank; Wavelet transform; Legendre wavelet; Algorithm; Discrete wavelet transform; Computer science; Computer vision","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":[0.0001851889,0.00008128171,0.00013581,0.00004455732,0.00005648709,0.00006623909,0.0003794508,0.000029893,0.0004908144],"category_scores_gemma":[0.00001472695,0.00006342913,0.0000782042,0.000137331,0.00003175947,0.0004723549,0.00005097308,0.00003689403,0.00001720702],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000004619451,"about_ca_system_score_gemma":0.00005121998,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003691652,"about_ca_topic_score_gemma":0.00000139666,"domain_scores_codex":[0.9993101,0.00004435358,0.0001676254,0.0001850332,0.0001337211,0.0001591999],"domain_scores_gemma":[0.9995046,0.00009157483,0.00003540549,0.000257147,0.00004895917,0.00006237471],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.000107572,0.00003190296,0.00001109634,0.00002484191,0.00001114546,0.000008322911,0.0003199572,0.00001989009,0.1145445,0.009792776,0.03190394,0.8432241],"study_design_scores_gemma":[0.002142094,0.0005124968,0.001449909,0.00007934991,0.0000141535,0.00007424606,0.0000212077,0.03289932,0.8488243,0.02746128,0.08611522,0.0004064635],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.003527862,0.00003688606,0.9874648,0.0006499288,0.00009117964,0.0001016823,0.000003982871,0.00006260624,0.008061085],"genre_scores_gemma":[0.006473181,0.000007060928,0.9777657,0.0002817695,0.0000459865,0.000003059458,0.000002611887,0.000005145561,0.01541547],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.8428177,"threshold_uncertainty_score":0.5374074,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02009706701519933,"score_gpt":0.2786173694573609,"score_spread":0.2585203024421616,"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."}}