{"id":"W2998181375","doi":"10.18280/ts.360609","title":"Wavelet-Based Self-adaptive Hierarchical Thresholding Algorithm and Its Application in Image Denoising","year":2019,"lang":"en","type":"article","venue":"Traitement du signal","topic":"Image and Signal Denoising Methods","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Key Science and Technology Program of Shaanxi Province","keywords":"Thresholding; Image denoising; Noise reduction; Artificial intelligence; Wavelet; Pattern recognition (psychology); Computer science; Image (mathematics); Non-local means; Algorithm; Step detection; Computer vision","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000560788,0.0002548093,0.0003886347,0.0005584852,0.0002380006,0.0003779983,0.000594712,0.0006507669,0.0007996895],"category_scores_gemma":[0.001155946,0.0002154014,0.0006195809,0.0007082665,0.0004052373,0.000742164,0.0004302961,0.000560711,0.0002791008],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003014096,"about_ca_system_score_gemma":0.0003510996,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001030328,"about_ca_topic_score_gemma":0.0009086754,"domain_scores_codex":[0.9996871,0.00005327831,0.00002158557,0.00006400009,0.0001523345,0.00002174928],"domain_scores_gemma":[0.9997223,0.00009587937,0.00003204541,0.00003631058,0.00009950185,0.00001388336],"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":[0.0001242918,0.00009410342,0.001516596,0.0003544138,0.00009953188,0.0002384528,0.0004230914,0.2708457,0.1765211,0.07124523,0.002575468,0.475962],"study_design_scores_gemma":[0.000007000614,0.000054506,0.0004015285,0.00001104448,0.00001912299,0.0001278404,0.00002401927,0.9765984,0.01465433,0.005389547,0.002698546,0.00001427379],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.009280093,0.0002496653,0.9893585,0.0000510227,0.00002199051,0.00001134026,0.000007228073,0.0001062808,0.0009137782],"genre_scores_gemma":[0.2720833,0.001028088,0.723473,0.00009497219,0.00006223322,0.00006633352,0.00008006908,0.00009494901,0.003017056],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.001030328,"threshold_uncertainty_score":0.002965748,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01332454519563768,"score_gpt":0.253761963544734,"score_spread":0.2404374183490963,"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."}}