{"id":"W1997653230","doi":"10.1109/tce.2007.381723","title":"Cascaded Neural Network-based S-VHS Restoration","year":2007,"lang":"en","type":"article","venue":"IEEE Transactions on Consumer Electronics","topic":"Image and Signal Denoising Methods","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Luminance; Image restoration; Artificial neural network; Computer science; Artificial intelligence; Computer vision; Image quality; Image (mathematics); Pattern recognition (psychology); Image processing","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":[0.0003038456,0.0004659061,0.0004367822,0.0004504615,0.0002307145,0.0002811001,0.0007363742,0.0006521574,0.002446624],"category_scores_gemma":[0.0006243578,0.0002348293,0.0004931627,0.0002833953,0.0003077343,0.000587562,0.0003369459,0.000531779,0.0006168181],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002934962,"about_ca_system_score_gemma":0.0004106872,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002028858,"about_ca_topic_score_gemma":0.003889639,"domain_scores_codex":[0.999828,0.0000232705,0.000009018665,0.00003677102,0.0000849828,0.00001788068],"domain_scores_gemma":[0.9997577,0.00005021461,0.00003220202,0.0000397147,0.0001021049,0.00001801608],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0004397682,0.0001521604,0.0008146497,0.000232861,0.00007058134,0.0002236589,0.00009993673,0.1178043,0.2053116,0.003789494,0.002453104,0.6686078],"study_design_scores_gemma":[0.0000196412,0.0001929202,0.0007486119,0.00001226893,0.00002831615,0.0002458312,0.00001311354,0.9412318,0.05375592,0.00078565,0.002946329,0.0000195969],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03793587,0.0004451943,0.9579534,0.00009746975,0.0001257415,0.00006348716,0.00003432351,0.0008268179,0.002517755],"genre_scores_gemma":[0.4173197,0.000507781,0.5715758,0.0001183517,0.00008599225,0.00006037008,0.0001280191,0.00006855913,0.01013535],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002446624,"threshold_uncertainty_score":0.008184791,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02189434947353174,"score_gpt":0.2817895220735612,"score_spread":0.2598951726000295,"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."}}