{"id":"W2161835923","doi":"10.1109/newcas.2006.250933","title":"A New Method for Denoising of Images in the Dual Tree Complex Wavelet Domain","year":2006,"lang":"en","type":"article","venue":"","topic":"Image and Signal Denoising Methods","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Noise reduction; Image denoising; Wavelet; Computer science; Dual (grammatical number); Artificial intelligence; Domain (mathematical analysis); Pattern recognition (psychology); Tree (set theory); Computer vision; Mathematics; Combinatorics","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":[0.002082644,0.0001169642,0.0002200386,0.0001212178,0.00007541934,0.00014509,0.0006583116,0.00003947715,0.00001981686],"category_scores_gemma":[0.00005657937,0.00007756936,0.0001010527,0.0004205201,0.0000302262,0.0002281792,0.00009015153,0.00007884301,0.000002466634],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001642866,"about_ca_system_score_gemma":0.0000640492,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009670464,"about_ca_topic_score_gemma":0.0001643086,"domain_scores_codex":[0.9985283,0.000403162,0.000314822,0.0002496577,0.0002388613,0.0002652013],"domain_scores_gemma":[0.998404,0.001049431,0.00008260056,0.0003821944,0.00005539619,0.00002639288],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0000487869,0.0001160018,0.00006426867,0.0000312524,0.00001231585,0.00004224132,0.001538051,0.0001131805,0.2361249,0.2489266,0.03390772,0.4790747],"study_design_scores_gemma":[0.004795078,0.0003637943,0.0212721,0.00004974128,0.00002951183,0.0001988058,0.0003685804,0.04699874,0.1746488,0.7313043,0.019401,0.0005696125],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001019783,0.00007233481,0.9852608,0.0019987,0.00005738573,0.0002195386,0.000001958497,0.00003486556,0.0113346],"genre_scores_gemma":[0.01430179,6.114827e-7,0.9838918,0.0005771685,0.0001049513,0.000006297661,0.000002295904,0.000007003545,0.001108045],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.4823777,"threshold_uncertainty_score":0.3163187,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03522689300066785,"score_gpt":0.3332364850127423,"score_spread":0.2980095920120745,"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."}}