{"id":"W2125058434","doi":"10.1007/s00034-015-0097-2","title":"Structuring of Contourlet Transform for Pipeline-Based Implementation","year":2015,"lang":"en","type":"article","venue":"Circuits Systems and Signal Processing","topic":"Advanced Image Fusion Techniques","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"McMaster University","funders":"","keywords":"Computer science; Contourlet; Pipeline (software); Quantization (signal processing); Field-programmable gate array; Computer hardware; Hardware architecture; Computer engineering; Artificial intelligence; Computer vision; Wavelet transform; Software; Wavelet","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":[0.0001465141,0.0004338359,0.0002448385,0.0004290587,0.0002916171,0.0006264001,0.0005390793,0.0003939252,0.006818851],"category_scores_gemma":[0.0004789816,0.0002297872,0.000314091,0.0004791533,0.000217398,0.0005745084,0.0004506398,0.0005958669,0.002100258],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002546403,"about_ca_system_score_gemma":0.0005952806,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005859408,"about_ca_topic_score_gemma":0.0007742583,"domain_scores_codex":[0.999891,0.00001306986,0.000008232391,0.00002173385,0.00004874557,0.00001713117],"domain_scores_gemma":[0.9998154,0.0000352612,0.00001434101,0.00005999146,0.00006526697,0.000009744667],"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":[0.0003400683,0.0001189688,0.0004919555,0.000154802,0.00002485947,0.0002437929,0.0002148273,0.02354771,0.4422122,0.04079439,0.007039257,0.4848172],"study_design_scores_gemma":[0.00004841404,0.0003182208,0.0008693622,0.00003358503,0.00003915095,0.0004393152,0.00005647277,0.5321819,0.4134042,0.01413744,0.03843952,0.00003233907],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01564076,0.0000856675,0.9797926,0.00005794011,0.00004063116,0.00004512677,0.00007826798,0.001122403,0.003136635],"genre_scores_gemma":[0.2056658,0.0002153361,0.78553,0.0001020103,0.00004791372,0.0001185216,0.0005660682,0.0002838766,0.007470569],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.006818851,"threshold_uncertainty_score":0.02281135,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02875242937816909,"score_gpt":0.2842482420800123,"score_spread":0.2554958127018432,"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."}}