{"id":"W101697707","doi":"10.1007/1-4020-4179-9_44","title":"VIRTUAL RESTORATION OF ARTWORKS USING ENTROPY-BASED COLOR IMAGE FILTERING SCHEMES","year":2006,"lang":"en","type":"book-chapter","venue":"Computational imaging and vision","topic":"Image and Signal Denoising Methods","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Artificial intelligence; Computer vision; Image restoration; Entropy (arrow of time); Image processing; Adaptive filter; Color image; Image (mathematics); Algorithm","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003615964,0.0002661959,0.0003229273,0.0003166674,0.0002060486,0.0002925297,0.000246747,0.0001010584,0.000008765017],"category_scores_gemma":[0.00003097252,0.0002759098,0.0001077805,0.00007436373,0.0001611575,0.0004828885,0.0001765613,0.0002256277,0.000005632411],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006553077,"about_ca_system_score_gemma":0.0001462523,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001275334,"about_ca_topic_score_gemma":2.612875e-7,"domain_scores_codex":[0.9984054,0.00006867179,0.0004496165,0.0004640684,0.0004367867,0.0001754775],"domain_scores_gemma":[0.9986708,0.0003213781,0.0003630884,0.0002403327,0.0003438835,0.00006049253],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002779263,0.0001934124,0.0001015025,0.0004529476,0.0001125674,0.0002808249,0.0003482146,0.4806094,0.08052593,0.1858164,0.01488107,0.2363998],"study_design_scores_gemma":[0.0006061961,0.00007681481,0.00008727432,0.0005478949,0.00002577777,0.00002341274,0.000001842063,0.9748387,0.00104114,0.01866417,0.003803024,0.0002837343],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0008900273,0.0005512624,0.994947,0.0001866903,0.0003394493,0.0001266139,0.00001152118,0.00008063882,0.002866814],"genre_scores_gemma":[0.06793124,0.00001090296,0.9254811,0.0002662166,0.0003503561,0.000002508593,0.0001776605,0.00005417088,0.005725809],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.4942293,"threshold_uncertainty_score":0.9999693,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02154834142195493,"score_gpt":0.309153558435985,"score_spread":0.28760521701403,"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."}}