{"id":"W4408037308","doi":"10.18280/ts.420106","title":"Image Denoising Algorithm Combining Noise Prior and Sparse Convolutional Self-Coding","year":2025,"lang":"en","type":"article","venue":"Traitement du signal","topic":"Image Processing Techniques and Applications","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Noise reduction; Image denoising; Computer science; Coding (social sciences); Neural coding; Artificial intelligence; Pattern recognition (psychology); Algorithm; Noise (video); Image (mathematics); Mathematics; Statistics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001628577,0.0001393688,0.0001282952,0.0001018353,0.0002192251,0.0001189188,0.0001044208,0.00004573806,0.00005826119],"category_scores_gemma":[0.000004369462,0.0001539358,0.00003161139,0.0001584556,0.00004884264,0.0001641485,0.00004527896,0.000131602,0.000008931829],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007536045,"about_ca_system_score_gemma":0.00002881582,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005327525,"about_ca_topic_score_gemma":5.840676e-7,"domain_scores_codex":[0.9992747,0.00001033576,0.0002194638,0.0001738524,0.0001103398,0.0002112856],"domain_scores_gemma":[0.9997429,0.00004128863,0.00002799723,0.00009147378,0.00004814622,0.00004824495],"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":[0.0000272093,0.0004862618,0.001549995,0.001157316,0.0004006312,0.00003548408,0.001783062,0.001038685,0.6093224,0.03028353,0.01749375,0.3364217],"study_design_scores_gemma":[0.001055469,0.00003072949,0.002870954,0.0002736132,0.0001046456,0.00001865859,0.0001178322,0.9552488,0.02517231,0.00302537,0.01167146,0.0004101041],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03523532,0.0003210223,0.9602387,0.0001760281,0.00006319564,0.0002575324,0.00001542534,0.0009152475,0.002777565],"genre_scores_gemma":[0.7736244,0.00004648673,0.2260204,0.0001045258,0.00005356264,0.00006580888,0.00001463307,0.000018164,0.00005195704],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9542102,"threshold_uncertainty_score":0.6277322,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008764455881695908,"score_gpt":0.2357599867086213,"score_spread":0.2269955308269254,"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."}}