{"id":"W2149875507","doi":"10.1109/ccece.1998.682709","title":"An information theoretic image-quality measure","year":2002,"lang":"en","type":"article","venue":"","topic":"Advanced Data Compression Techniques","field":"Computer Science","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Lossy compression; Measure (data warehouse); Computer science; Artificial intelligence; Image quality; Image compression; Mean squared error; Encoding (memory); Representation (politics); Data compression; Image (mathematics); Information theory; Pattern recognition (psychology); Computer vision; Image processing; Mathematics; Data mining; Statistics","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":[0.003640055,0.001131261,0.001111748,0.004365575,0.0003671808,0.002475691,0.001327575,0.001696342,0.001948266],"category_scores_gemma":[0.0132196,0.0002588395,0.0005818984,0.002426252,0.002007418,0.004785688,0.001569592,0.001267585,0.000821243],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0012119,"about_ca_system_score_gemma":0.0006238347,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003557071,"about_ca_topic_score_gemma":0.0002827338,"domain_scores_codex":[0.9948754,0.001016547,0.0003484524,0.0005307547,0.003102327,0.0001266537],"domain_scores_gemma":[0.9931782,0.002695582,0.001072841,0.0007322978,0.002108754,0.0002122805],"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":[0.0005544884,0.0003041051,0.007651412,0.002105106,0.0006218419,0.0003986532,0.0003561926,0.1060236,0.09395006,0.2782709,0.0118135,0.4979501],"study_design_scores_gemma":[0.00009056149,0.001826653,0.0168044,0.0004697002,0.0004105618,0.00402388,0.0003347267,0.6321923,0.06988789,0.2212207,0.05227639,0.0004622185],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01285998,0.004899057,0.9750288,0.0003558203,0.0002367155,0.0001126856,0.0004057396,0.0003412118,0.005760009],"genre_scores_gemma":[0.4796562,0.004064368,0.5091112,0.0004753644,0.0007825436,0.0004006329,0.001300912,0.0002226417,0.003986234],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.004365575,"threshold_uncertainty_score":0.01925069,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0231913388971485,"score_gpt":0.299273327553619,"score_spread":0.2760819886564705,"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."}}